Skip to content
Computer Vision Group

TAU Computing Sciences

Publications

2024

  • NN-VVC: A hybrid learned-conventional video codec targeting humans and machines (Ahonen J., Le N., Zhang H., Hallapuro A., Cricri F., Tavakoli H., Hannuksela M. and Rahtu E.), In , volume , 2024. [doi]
  • Synchformer: Efficient synchronization from sparse cues (Iashin V., Xie W., Rahtu E. and Zisserman A.), In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024. [url]
  • Raspberry Pi -varashälytin (Markus Pellinen), Technical report, Tampere University, 2024. [url]
  • PlaceNav: Topological Navigation through Place Recognition (L. Suomela, J. Kalliola, H. Edelman and J.-K. Kämäräinen), In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2024. [url] [code]
  • MuSHRoom: Multi-Sensor Hybrid Room Dataset for Joint 3D Reconstruction and Novel View Synthesis (Ren X., Wang W., Cai D., Tuominen T., Kannala J. and Rahtu E.), In IEEE Winter Conference on Applications of Computer Vision (WACV), 2024. [url]
  • Gaussian Splatting on the Move: Blur and Rolling Shutter Compensation for Natural Camera Motion (Seiskari O., Ylilammi J., Kaatrasalo V., Rantalankila P., Turkulainen M., Kannala J., Rahtu E. and Solin A.), In European Conference on Computer Vision (ECCV), 2024.
  • Image Classification in the Fourier Domain (Mikko Suominen), Technical report, Tampere University, 2024. [url]
  • DAVIDE: Depth-Aware Video Deblurring (German F. Torres, J. Kalliola, S. Tripathy, E. Acar, and J.-K. Kämäräinen), In Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 2024.
  • Probabilistic Subgoal Representations for Hierarchical Reinforcement learning (V. H. Wang, T. Wang, W. Yang, J.-K. Kamarainen and J. Pajarinen), In Proceedings of the Forty-first International Conference on Machine Learning (ICML), 2024.

2023

  • Region of Interest Enabled Learned Image Coding for Machines (Ahonen J., Le N., Cricri F. and Rahtu E.), In The IEEE International Workshop on Multimedia Signal Processing (MMSP), 2023.
  • Long-term Visual Place Recognition Under Varying Conditions (Farid Alijani), PhD thesis, Tampere University, 2023. [url]
  • MSDA: Monocular Self-supervised Domain Adaptation for 6D Object Pose Estimation (Cai D., Heikkilä J. and Rahtu E.), In Scandinavian Conference on Image Analysis (SCIA), 2023. [pdf]
  • TAU-Indoors Dataset for Visual and LiDAR Place Recognition (Dag A., Alijani F., Peltomäki J., Suomela L., Rahtu E., Edelman H. and Kämäräinen J.), In Scandinavian Conference on Image Analysis (SCIA), 2023. [url]
  • TAU-Indoors Dataset for Visual and LiDAR Place Recognition (Atakan Dag, Farid Alijani, Jukka Peltomaki, Lauri Suomela, Esa Rahtu, Harry Edelman and J.-K. Kämäräinen), In Scandinavian Conf. on Image Analysis (SCIA), 2023. [pdf]
  • Visual Anomaly Detection and Localization with a Patch-Wise Transformer and Convolutional Model (Afshin D. and Rahtu E.), In International Conference on Computer Vision Theory and Applications (VISAPP), 2023.
  • IFMix: Utilizing Intermediate Filtered Images for Domain Adaptation in Classification (Germi S. and Rahtu E.), In International Conference on Computer Vision Theory and Applications (VISAPP), 2023.
  • Momentum Adapt: Robust Unsupervised Adaptation for Improving Temporal Consistency in Video Semantic Segmentation During Test-Time (Hassankhani A., Tavakoli H. and Rahtu E.), In British Machine Vision Conference (BMVC), 2023. [url]
  • On Deep Image Deblurring: The Blur Factorization Approach (Samuli Hynninen), Master’s thesis, Tampere University, 2023. [url]
  • SLAM Drift and Localization Error Reduction with RTAB-Map tools (Siina Ingren), Technical report, Tampere University, 2023. [url]
  • Animation of a speaking chatbot (Konsta Jurvanen), Technical report, Tampere University, 2023. [url] [code]
  • Koneoppimisen perusteet (Joni Kämäräinen), Gaudeamus, 2023. [url]
  • NVIDIA Isaac and Robot Operating System 2 : Integrating ROS2 with Isaac Sim for robot navigation (Dan Katainen), Technical report, Tampere University, 2023. [url]
  • Drift Correction for SLAM Point Clouds: Smooth Natural Neighbor Interpolation (Kaapo Kontinen), Technical report, Tampere University, 2023. [url] [code]
  • Single Pixel Spectral Color Constancy (S. Koskinen, E. Acar and J.-K. Kämäräinen), In International Journal of Computer Vision, 2023. [doi]
  • FinnWoodlands Dataset (Lagos J., Lempiö U. and Rahtu E.), In Scandinavian Conference on Image Analysis (SCIA), 2023. [url]
  • Image Morphing Sequences (Henrik Lauronen), Technical report, Tampere University, 2023. [url]
  • BS3D: Building-scale 3D Reconstruction from RGB-D Images (Mustaniemi J., Kannala J., Rahtu E., Liu L. and Heikkilä J.), In Scandinavian Conference on Image Analysis (SCIA), 2023. [pdf]
  • Cascaded and Generalizable Neural Radiance Fields for Fast View Synthesis (Nguyen P, Huynh L., Rahtu E., Matas J. and Heikkilä J.), In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), volume , 2023. [url] [doi]
  • Raspberry Pi Art Display with Neural Style Transfer (Aleksi Nissilä), Technical report, Tampere University, 2023. [url] [code]
  • Toward Verifiable and Reproducible Human Evaluation for Text-to-Image Generation (Otani M., Togashi R., Sawai Y., Ishigami R., Nakashima Y., Rahtu E., Heikkilä J. and Satoh S.), In The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023. [pdf]
  • LiDAR Place Recognition Evaluation with the Oxford Radar RobotCar Dataset Revised (Peltomäki J., Alijani F., Puura J., Huttunen H., Rahtu E. and Kämäräinen J.), In Scandinavian Conference on Image Analysis (SCIA), 2023. [url]
  • LiDAR Place Recognition Evaluation with the Oxford Radar RobotCar Dataset Revised (J. Peltomäki, F. Alijani, J. Puura, H. Huttunen, E. Rahtu and J.-K. Kämäräinen), In Scandinavian Conf. on Image Analysis (SCIA), 2023. [pdf]
  • LiDAR Place Recognition with Image Retrieval (Jukka Peltomäki), PhD thesis, Tampere University, 2023. [url]
  • Deep Learning with Fourier Transformed Images (Noora Sassali), Technical report, Tampere University, 2023. [url] [code]
  • Spoken Wake-word Detection for Conversational Avatar (Simon Savukoski), Technical report, Tampere University, 2023. [url] [code]
  • Frequency Domain Image Classification with Convolutional Neura Networks (Sophie Tötterström), Technical report, Tampere University, 2023. [url] [code]
  • Benchmarking Visual Localization for Autonomous Navigation (L. Suomela, J. Kalliola, A. Dag, H. Edelman and J.-K. Kämäräinen), In IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023. [code]
  • Depth-aware Image Compositing Model for Parallax Camera Motion Blur (G.F. Torres and J.-K. Kämäräinen), In Scandinavian Conference on Image Analysis (SCIA), 2023. [url] [code]
  • A Depth Backbone for Image Classification (Ville Vianto), Technical report, Tampere University, 2023. [url]
  • State-conditioned Adversarial Subgoal Generation (H. Wang, J. Pajarinen, T. Wang and J.-K. Kämäräinen), In Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023. [url]
  • Prioritized offline Goal-swapping Experience Replay (W. Yang, J. Pajarinen and J.-K. Kämäräinen), In Int. Conf. On Learning Representations Workshops (ICLRW), 2023. [url]
  • Seq2Seq Imitation Learning for Manipulation with Tactile Feedback (W. Yang, A. Angleraud, R.S. Pieters, J. Pajarinen and J.-K. Kämäräinen), In IEEE Int. Conf. on Robotics and Automation (ICRA), 2023. [url] [youtube]
  • 22nd Scandinavian Conf. on Image Analysis, (R. Gade, M. Felsberg, J.-K. Kämäräinen, eds.), Springer, 2023. [url]

2022

  • Evaluation of RGB and LiDAR Combination for Robust Place Recognition (Alijani F., Peltomäki J., Puura J., Huttunen H., Kämäräinen J. and Rahtu E.), In International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP), 2022.
  • Long-Term Visual Place Recognition (F. Alijani, J- Peltomäki, J. Puura, H. Huttunen, J.-K. Kämäräinen and E. Rahtu), In Int. Conf. on Pattern Recognition (ICPR), 2022. [pdf]
  • OVE6D: Object Viewpoint Encoding for Depth-based 6D Object Pose Estimation (Cai D., Heikkilä J. and Rahtu E.), In The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [url]
  • SC6D: Symmetry-agnostic and Correspondence-free 6D Object Pose Estimation (Cai D., Heikkilä J. and Rahtu E.), In International Conference on 3D Vision 2021 (3DV), 2022. [url]
  • Camera Pose Estimation from Street-view Snapshots and Point Clouds (Junsheng Fu), PhD thesis, Tampere University, 2022. [url]
  • A Practical Overview of Safety Concerns and Mitigation Methods for Visual Deep Learning Algorithms (Germi S. and Rahtu E.), In SafeAI: The AAAI’s Workshop on Artificial Intelligence Safety, 2022.
  • Lightweight Monocular Depth with a Novel Neural Architecture Search Method (Huynh L., Nguyen P., Matas J., Rahtu E. and Heikkilä J.), In IEEE Winter Conference on Applications of Computer Vision (WACV), 2022. [pdf]
  • Sparse in Space and Time: Audio-visual Synchronisation with Trainable Selectors (Iashin V., Xie W., Zisserman A. and Rahtu E.), In British Machine Vision Conference (BMVC), 2022. [pdf]
  • Estimating three-dimensional motion using IMU sensors (Marko Kivikangas), Technical report, Tampere University, 2022. [url]
  • Vision Based Autonomous Driving : Hardware and Software Implementation (Olli Koskelainen), Technical report, Tampere University, 2022. [url]
  • The Tenth Visual Object Tracking VOT2022 Challenge Results (Matej Kristan, Ales Leonardis, Jiri Matas, Michael Felsberg, Roman Pflugfelder, Joni-Kristian Kamarainen, Hyung Jin Chang, Martin Danelljan, Luka Č Zajc, Alan Luke\vzič, Ondrej Drbohlav, Johanna Bjorklund, Yushan Zhang, Zhongqun Zhang, Song Yan, Wenyan Yang, Dingding Cai, Christoph Mayer and Gustavo Fernandez), In Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 2022. [url]
  • Adaptive Monte Carlo Localization in ROS (Tuomas Lauttia), Technical report, Tampere University, 2022. [url]
  • Bridging the Gap Between Image Coding for Machines and Humans (Le N., Zhang H., Cricri F., Youvalari R., Tavakoli H., Aksu E., Hannuksela M. and Rahtu E.), In The IEEE International Conference on Image Processing (ICIP), 2022.
  • Living in the Line World: How life would be in a world where we could merely perceive edges (Anni Lignell), Technical report, Tampere University, 2022. [url]
  • Visual Localization Using Mobile Phone (Joona Nousiainen), Technical report, Tampere University, 2022. [url] [code]
  • Optimal Correction Cost for Object Detection Evaluation (Otani M., Togashi R., Nakashima Y., Rahtu E., Heikkilä J. and Satosh S.), In The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [url]
  • Online panoptic 3D reconstruction as a Linear Assignment Problem (Raivio L. and Rahtu E.), In International Conference on Image Analysis and Processing (ICIAP), 2022. [url]
  • Robotic grasping in agile production (Sefat A., Ahmad S., Angleraud A., Rahtu E and Pieters R.), In Deep Learning for Robot Perception and Cognition, 2022.
  • HybVIO: Pushing the Limits of Real-time Visual-inertial Odometry (Seiskari O., Rantalankila P., Kannala J., Ylilammi J., Rahtu E. and Solin A.), In IEEE Winter Conference on Applications of Computer Vision (WACV), 2022. [url]
  • Visual Rewards from Observation for Sequential Tasks: Autonomous Pile Loading (N. Strokina, W. Yang, J. Pajarinen, N. Serbenyuk, J.-K. Kämäräinen and R. Ghabcheloo), In Frontiers in Robotics and AI, 2022. [doi]
  • AxIoU: An Axiomatically Justified Measure for Video Moment Retrieval (Togashi R., Otani M., Nakashima Y., Rahtu E., Heikkilä J. and Sakai T.), In The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [url]
  • Single Source One Shot Reenactment using Weighted motion From Paired Feature Points (Tripathy S., Kannala J. and Rahtu E.), In IEEE Winter Conference on Applications of Computer Vision (WACV), 2022. [url]
  • Vision and Depth Based Computerized Anthropometry and Object Tracking (Song Yan), PhD thesis, Tampere University, 2022. [url]
  • Active Short-Long Exposure Deblurring (D. Yang, S. Koskinen and J.-K. Kämäräinen), In Int. Conf. on Pattern Recognition (ICPR), 2022. [pdf]
  • Constrained Imitation Q-learning with Earth Mover’s Distance reward (W. Yang, N. Strokina, J. Pajarinen and J.-K. Kämäräinen), In Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS) Workshop on Deep Reinforcement Learning, 2022. [url]
  • Visually Guided Sound Source Separation and Localization using Self-Supervised Motion Representations (Zhu L. and Rahtu E.), In IEEE Winter Conference on Applications of Computer Vision (WACV), 2022. [pdf]
  • V-SlowFast Network for Efficient Visual Sound Separation (Zhu L. and Rahtu E.), In IEEE Winter Conference on Applications of Computer Vision (WACV), 2022. [url]
  • Region of Interest Enabled Learned Image Coding for Machines (Zou N., Cricri F., Zhang H., Tavakoli H., Hannuksela M. and Rahtu E.), In The IEEE International Symposium on Multimedia (ISM), 2022.

2021

  • Towards a Real-Time Facial Analysis System (Adhikari B., Ni X., Rahtu E. and Huttunen H.), In IEEE International Workshop on Multimedia Signal Processing (MMSP), 2021. [url]
  • Effect of Label Noise on Robustness of Deep Neural Network Object Detectors (Adhikari B., Peltomäki J., Germi S., Rahtu E. and Huttunen H.), In International Conference on Computer Safety, Reliability, and Security, 2021.
  • Sample selection for efficient image annotation (Adhikari B., Rahtu E. and Huttunen H.), In European Workshop on Visual Information Processing (EUVIP), 2021. [url]
  • Automatic Dataset Generation From CAD for Vision-Based Grasping (Ahmad S., Samarawickrama K., Rahtu E and Pieters R.), In International Conference on Advanced Robotics (ICAR), 2021.
  • Monolithic vs. Hybrid Controller for Multi-objective Sim-to-Real Learning (A. Dag, A. Angleraud, W. Yang, N. Strokina, R.S. Pieters, M. Lanz and J.-K. Kämäräinen), In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021. [pdf] [code]
  • Comparison of monolithic and hybrid controllers for multi-objective sim-to-real learning (Atakan Dag), Master’s thesis, Tampere University, 2021. [url] [code]
  • Selective Probabilistic Classifier Based on Hypothesis Testing (Germi S., Rahtu E. and Huttunen H.), In European Workshop on Visual Information Processing (EUVIP), 2021. [url]
  • FATALRead – Fooling visual speech recognition models (Gupta A., Gupta P. and Rahtu E.), In Applied Intelligence, 2021. [url]
  • Deep Open Domain Chatbots (Tariq Harb), Technical report, Tampere University, 2021. [url] [code]
  • Computer Vision for Robotics: Feature Matching, Pose Estimation and Safe Human-Robot Collaboration (Antti Hietanen), PhD thesis, Tampere University, 2021. [url]
  • Benchmarking Pose Estimation for Robot Manipulation (A. Hietanen, J. Latokartano, A. Foi, R. Pieters, V. Kyrki, M. Lanz and J.-K. Kämäräinen), In Robotics and Autonomous Systems, 2021. [doi] [code] [data]
  • Boosting Monocular Depth Estimation with Lightweight 3D Point Fusion (Huynh L., Nguyen P., Matas J., Rahtu E. and Heikkilä J.), In International Conference on Computer Vision (ICCV), 2021. [pdf]
  • Monocular Depth Estimation Primed by Salient Point Detection and Normalized Hessian Loss (Huynh L., Pedone M., Nguyen P., Matas J., Rahtu E. and Heikkilä J.), In International Conference on 3D Vision 2021 (3DV), 2021. [url]
  • Taming Visually Guided Sound Generation (Iashin V. and Rahtu E.), In British Machine Vision Conference (BMVC), 2021. [url]
  • Single Pixel Spectral Color Constancy (S. Koskinen, E. Acar and J.-K. Kämäräinen), In British Machine Vision Conference (BMVC), 2021. [html]
  • Image coding for machines: An end-to-end learned approach (Le N., Zhang H., Cricri F., Ghaznavi-Youvalari R. and Rahtu E.), In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021. [url]
  • Learned Image Coding for Machines: A Content-Adaptive Approach (Le N., Zhang H., Cricri F., Ghaznavi-Youvalari R., H. Tavakoli and Rahtu E.), In IEEE International Conference on Multimedia and Expo (ICME), 2021. [url]
  • Automatic Knee Osteoarthritis Diagnosis from Plain Radiographs: A Deep Learning-Based Approach. (Ligocki A., Jelinek A., Zalud L. and Rahtu E.), In Sensors, volume 21, 2021. [url]
  • RGBD-Net: Predicting Color and Depth images for Novel Views Synthesis (Nguyen P., Karnewar A., Huynh L., Rahtu E., Matas J. and Heikkilä J.), In International Conference on 3D Vision 2021 (3DV), 2021. [url]
  • On the Importance of Encrypting Deep Features (Ni X., Huttunen H. and Rahtu E.), In The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2021. [pdf]
  • FlipReID: Closing the Gap between Training and Inference in Person Re-Identification (Ni X. and Rahtu E.), In European Workshop on Visual Information Processing (EUVIP), 2021. [url]
  • Evaluation of Long-term LiDAR Place Recognition (Peltomäki J., Alijani F., Puura J., Huttunen H., Rahtu E. and Kämäräinen J.-K.), In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021.
  • Evaluation of Long-term LiDAR Place Recognition (J. Peltomäki, F. Alijani, J. Puura, H. Huttunen, E. Rahtu and J.-K. Kämäräinen), In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021. [pdf]
  • Fast Fourier Intrinsic Network (Y. Qian, M. Shi, J.-K. Kämäräinen and J. Matas), In IEEE Winter Conference on Applications of Computer Vision (WACV), 2021. [pdf]
  • Implementing HR analytics: Premises for value creating analytics (Lauri A. Suomela), Master’s thesis, Tampere University, 2021. [url]
  • FACEGAN: Facial Attribute Controllable rEenactment GAN. (Tripathy S., Kannala J. and Rahtu E.), In IEEE Winter Conference on Applications of Computer Vision (WACV), 2021. [url]
  • Vision-based Body Measurements (Jori Väinölä), Technical report, Tampere University, 2021. [url] [code]
  • Depth-only Object Tracking (S. Yan, J. Yang, A. Leonardis and J.-K. Kämäräinen), In British Machine Vision Conference (BMVC), 2021. [pdf] [code]
  • DepthTrack: Unveiling the Power of RGBD Tracking (S. Yan, J. Yang, J. Käpylä, F. Zheng, A. Leonardis and J.-K. Kämäräinen), In Int. Conf. on Computer Vision (ICCV), 2021. [pdf] [code]
  • Neural Network Controller for Autonomous Pile Loading Revised (W. Yang, N. Strokina, N. Serbenyuk, J. Pajarinen, R. Ghabcheloo, J. Vihonen, M.M. Aref and J.-K. Kämäräinen), In IEEE Int. Conf. on Robotics and Automation (ICRA), 2021. [url] [youtube]
  • Leveraging Category Information for Single-Frame Visual Sound Source Separation (Zhu L. and Rahtu E.), In European Workshop on Visual Information Processing (EUVIP), 2021. [url]
  • Learned Video Compression With Intra-Guided Enhancement and Implicit Motion Information (Zou N., Zhang H., Cricri F., Tavakoli HR., Lainema J., Aksu E., Hannuksela M. and Rahtu E.), In The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2021. [pdf]
  • The Ninth Visual Object Tracking VOT2021 Challenge Results (Kristan, Matej, Matas, Ji\vrí, Leonardis, Aleš, Felsberg, Michael, Pflugfelder, Roman, Kämäräinen, Joni-Kristian, Chang, Hyung Jin, Danelljan, Martin, Cehovin, Luka, Luke\vzič, Alan, Drbohlav, Ondrej, Käpylä, Jani, Häger, Gustav, Yan, Song, Yang, Jinyu, Zhang, Zhongqun and Fernández, Gustavo), In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2021. [html]

2020

  • Deep Learning Off-the-shelf Holistic Feature Descriptors for Visual Place Recognition in Challenging Conditions (Alijani F. and Rahtu E.), In The IEEE International Workshop on Multimedia Signal Processing (MMSP), 2020.
  • AR-based Interaction for Human-robot Collaboration (A. Hietanen, R. Pieters, M. Lanz, J. Latokartano and J.-K. Kämäräinen), In Robotics and Computer-Integrated Manufacturing, volume 63, 2020. [doi] [youtube]
  • Guiding Monocular Depth Estimation Using Depth Attention-Volume (Huynh L., Nguyen P., Matas J., Rahtu E. and Heikkilä J.), In European Conference on Computer Vision (ECCV), 2020.
  • Multi-Modal Dense Video Captioning (Iashin V. and Rahtu E.), In The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020. [html]
  • A Better Use of Audio-Visual Cues: Dense Video Captioning with Bi-modal Transformer (Iashin V. and Rahtu E.), In British Machine Vision Conference (BMVC), 2020. [url]
  • Smoke and Fire Segmentation from Images Using Weakly Supervised Neural Networks (Raafael Juntti), Technical report, Tampere University, 2020. [url]
  • Simultaneous Localization and Mapping with Apple ARKit (Christian Kaarre), Technical report, Tampere University, 2020. [url] [code] [youtube]
  • Cross-dataset Color Constancy Revisited Using Sensor-to-Sensor Transfer (S. Koskinen, D. Yang and J.-K. Kämäräinen), In British Machine Vision Conference (BMVC), 2020. [pdf]
  • The Eighth Visual Object Tracking VOT2020 Challenge Results (Matej Kristan, Ales Leonardis, Jiri Matas, Michael Felsberg, Roman Pflugfelder, Joni-Kristian Kamarainen, Luka Č Zajc, Martin Danelljan, Alan Lukezic, Ondrej Drbohlav, Linbo He, Yushan Zhang, Song Yan, Jinyu Yang, Gustavo Fernandez and et al.), In European Conference on Computer Vision (ECCV) Workshops, 2020. [url]
  • Autonomous Racing Robot: Hardware and Software Implementation (Eetu Manninen), Technical report, Tampere University, 2020. [url] [code]
  • Sequential View Synthesis with Transformer (Nguyen P., Huynh L., Rahtu E. and Heikkilä J.), In Asian Conference on Computer Vision (ACCV), 2020.
  • Uncovering Hidden Challenges in Query-Based Video Moment Retrieval (Otani M., Nakashima Y., Heikkilä J. and Rahtu E.), In British Machine Vision Conference (BMVC), 2020.
  • Loop-closure detection by LiDAR scan re-identification (J. Peltomäki, X. Ni, J. Puura, J.-K. Kämäräinen and H. Huttunen), In Int. Conf. on Pattern Recognition (ICPR), 2020. [pdf]
  • A Benchmark for Burst Color Constancy (Y. Qian, J. Käpylä, J.-K. Kämäräinen, S. Koskinen and J. Matas), In European Conference on Computer Vision (ECCV) Workshops, 2020. [url]
  • DAL: A Deep Depth-Aware Long-term Tracker (Y. Qian, S. Yan, A. Lukezic, M. Kristan, J.-K. Kämäräinen and J. Matas), In Int. Conf. on Pattern Recognition (ICPR), 2020. [pdf] [doi] [code]
  • Computational Color Constancy: From Pixel to Video with a Stop at Convolutional Neural Network (Yanlin Qian), PhD thesis, Tampere University, 2020. [url]
  • Learning to Align Images (Eero Ruuhikorpi), Technical report, Tampere University, 2020. [url] [code]
  • Deep Audio-Visual Saliency: Baseline Model and Data. (Tavakoli HR., Borji A., Rahtu E. and Kannala J.), In ACM Symposium on Eye Tracking Research & Applications (ETRA), 2020.
  • ICface: Interpretable and Controllable Face Reenactment Using GANs. (Tripathy S., Kannala J. and Rahtu E.), In IEEE Winter Conference on Applications of Computer Vision (WACV), 2020.
  • Implementing VR feature camera on Android platform (Aleksi Viljanen), Technical report, Tampere University, 2020. [url] [code]
  • Silhouette Body Measurement Benchmarks (S. Yan, J. Wirta and J.-K. Kämäräinen), In Int. Conf. on Pattern Recognition (ICPR), 2020. [pdf] [doi] [data]
  • Anthropometric clothing measurements from 3D body scans (S. Yan, J. Wirta and J.-K. Kämäräinen), In Machine Vision and Applications, volume 31, 2020. [url] [doi] [data]
  • Learning a Pile Loading Controller from Demonstrations (W. Yang, N. Strokina, N. Serbenyuk, R. Ghabcheloo and J.-K. Kämäräinen), In IEEE Int. Conf. on Robotics and Automation (ICRA), 2020. [pdf] [doi] [youtube]
  • Visually Guided Sound Source Separation using Cascaded Opponent Filter Network (Zhu L. and Rahtu E.), In Asian Conference on Computer Vision (ACCV), 2020url=https://arxiv.org/abs/2006.03028.
  • End-to-End Learning for Video Frame Compression with Self-Attention (Zou N., Zhang H., Cricri F., Tavakoli HR., Lainema J., Aksu E., Hannuksela M. and Rahtu E.), In The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020.
  • L2C – Learning to Learn to Compress (Zou N., Zhang H., Cricri F., Tavakoli HR., Lainema J., Hannuksela M., Aksu E. and Rahtu E.), In The IEEE International Workshop on Multimedia Signal Processing (MMSP), 2020.

2019

  • Smartphone Teleoperation for Self-Balancing Telepresence Robots (A.E. Ainasoja, S. Pertuz and J.-K. Kämäräinen), In Int. Conf. on Computer Vision Theory and Applications (VISAPP), 2019. [pdf] [youtube]
  • Visual Reward for Autonomous Driving (Lauri Alho), Technical report, Tampere University, 2019. [url]
  • Kuvan korjaaminen ilman sen näkemistä (Jani Brjörklund), Technical report, Tampere University, 2019. [url]
  • Cumulative Attribute Space Regression for Head Pose Estimation and Color Constancy (K. Chen, K. Jia, H. Huttunen, J. Matas and J.-K. Kämäräinen), In Pattern Recognition, volume 87, 2019. [pdf] [doi]
  • Performance Analysis of Single-query 6-DoF Camera Pose Estimation in Self-Driving Setups (J. Fu, S. Pertuz, J. Matas and J.-K. Kämäräinen), In Computer Vision and Image Understanding, 2019. [pdf] [doi] [code]
  • CIIDefence: Defeating Adversarial Attacks by Fusing Class-specific Image Inpainting and Image Denoising. (Gupta P. and Rahtu E.), In IEEE International Conference on Computer Vision (ICCV), 2019.
  • MLAttack: Fooling Semantic Segmentation Networks by Multi-layer Attacks. (Gupta P. and Rahtu E.), In German Conference on Pattern Recognition (GCPR), 2019.
  • Neural Network Pile Loading Controller Trained by Demonstration (E. Halbach, J.-K. Kämäräinen and R. Ghabcheloo), In IEEE Int. Conf. on Robotics and Automation (ICRA), 2019. [pdf] [youtube]
  • Proof of concept of a projection-based safety system for human-robot collaborative engine assembly (A. Hietanen, A. Changizi, M. Lanz, J.-K. Kämäräinen, P. Ganguly, R. Pieters and J. Latokartano), In IEEE Int. Conf. on Robot & Human Interactive Communication (RO-MAN), 2019. [pdf]
  • Object Tracking by Reconstruction with View-Specific Discriminative Correlation Filters (U. Kart, A. Lukezic, M. Kristan, J.-K. Kämäräinen and J. Matas), In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2019. [pdf] [code]
  • Reverse Imaging Pipeline for Raw RGB Image Augmentation (S. Koskinen, D. Yang and J.-K. Kämäräinen), In Int. Conf. on Image Processing (ICIP), 2019. [pdf]
  • The Seventh Visual Object Tracking VOT2019 Challenge Results (Kristan, Matej, Matas, Jiri, Leonardis, Ales, Felsberg, Michael, Pflugfelder, Roman, Kamarainen, Joni-Kristian, Cehovin Zajc, Luka, Drbohlav, Ondrej, Lukezic, Alan, Berg, Amanda, Eldesokey, Abdelrahman, Kapyla, Jani, Fernandez, Gustavo, Gonzalez-Garcia, Abel, Memarmoghadam, Alireza, Lu, Andong, He, Anfeng, Varfolomieiev, Anton, Chan, Antoni, Shekhar Tripathi, Ardhendu, Smeulders, Arnold, Suraj Pedasingu, Bala, Xin Chen, Bao, Zhang, Baopeng, Wu, Baoyuan, Li, Bi, He, Bin, Yan, Bin, Bai, Bing, Li, Bing, Li, Bo, Hak Kim, Byeong and Hak Ki, Byeong), In The IEEE International Conference on Computer Vision (ICCV) Workshops, 2019. [pdf]
  • Portrait Instance Segmentation for Mobile Devices (L. Zhu, T: Wang, E. Aksu and J.-K. Kämäräinen), In IEEE Int. Conf. on Multimedia and Expo (ICME), 2019. [pdf]
  • CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark (A. Lukezic, U. Kart, J. Käpylä, A. Durmush, J.-K. Kämäräinen, J. Matas and M. Kristan), In Int. Conf. on Computer Vision (ICCV), 2019. [pdf] [code]
  • DGC-Net: Dense Geometric Correspondence Network. (Melekhov I., Tiulpin A., Sattler T., Pollefeys M., Rahtu E. and Kannala J.), In IEEE Winter Conference on Applications of Computer Vision (WACV), 2019.
  • Predicting Novel Views Using Generative Adversarial Query Network. (Nguyen-Ha P., Huynh L., Rahtu E. and Heikkilä J.), In Scandinavian Conference on Image Analysis (SCIA), 2019.
  • Rethinking the Evaluation of Video Summaries. (Otani M., Nakashima Y., Heikkilä J. and Rahtu E.), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
  • Open Framework for Mammography-based Breast Cancer Risk Assessment (S. Pertuz, G.F. Torres, R. Tamimi and J.-K. Kämäräinen), In IEEE-EMBS Int. Conf. on Biomedical and Healtch Informatics (BHI), 2019. [pdf] [code]
  • Micro-parenchymal patterns for breast cancer risk assessment (S. Pertuz, A. Sassi, M. Karivaara-Makela, K. Holli-Helenius, A.-L. Laaperi, I. Rinta-Kiikka, O. Arponen and J.-K. Kämäräinen), In Biomedical Physics & Engineering Express, 2019. [doi]
  • Clinical evaluation of a fully-automated parenchymal analysis software for breast cancer risk assessment: A pilot study in a Finnish sample (S. Pertuz, A. Sassi, K. Holli-Helenius, J.-K. Kämäräinen, I. Rinta-Kiikka, A.-L. Lääperi and O. Arponen), In European Journal of Radiology, volume 121, 2019. [doi]
  • Anki Cozmo -ohjelmointi (Kirsi Pietilä), Technical report, Tampere University, 2019. [url]
  • On Finding Gray Pixel (Y. Qian, J.-K. Kämäräinen, J. Nikkanen and J. Matas), In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2019. [pdf] [code]
  • Flash Lightens Gray Pixels (Y. Qian, S. Yan, J.-K. Kämäräinen and J. Matas), In Int. Conf. on Image Processing (ICIP), 2019. [pdf]
  • Beyond Wisdom of Crowds: Deep Uncertainty Coding for Apparent Age Estimation (Y. Qian, Ke Chen, D. Yang and J.-K. Kämäräinen), In IEEE 4th International Conference on Image, Vision and Computing (ICIVC), 2019.
  • Revisiting Gray Pixel for Statistical Illumination Estimation (Y. Qian, S. Pertuz, J. Nikkanen, J.-K. Kämäräinen and J. Matas), In Int. Conf. on Computer Vision Theory and Applications (VISAPP), 2019. (Nominee for the Best Student Paper Award) [url]
  • Trend Analysis in AI Research Over Time Using NLP Techniques (Eemeli Saari), Technical report, Tampere University, 2019. [url]
  • Digging Deeper Into Egocentric Gaze Prediction. (Tavakoli HR., Rahtu E., Kannala J. and Borji A.), In IEEE Winter Conference on Applications of Computer Vision (WACV), 2019.
  • Multimodal machine learning-based knee osteoarthritis progression prediction from plain radiographs and clinical data. (Tiulpin A., Klein S., Bierma-Zeinstra S., Thevenot J., Rahtu E., Meurs J., Oei E. and Saarakkala S.), In Scientific reports, volume 9, 2019.
  • Morphological Area Gradient: System-Independent Dense Tissue Segmentation in Mammography Images (G.F. Torres, A. Sassi, O. Arponen, K. Holli-Helenius, A.-L. Laaperi, I. Rinta-Kiikka, J.-K. Kämäräinen and S. Pertuz), In 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2019.
  • UR5-robottikäden reaaliaikainen ohjaus (Valtteri Viikari), Technical report, Tampere University, 2019. [url]
  • CNN-based Cross-dataset No-reference Image Quality Assessment (D. Yang, V.-T. Peltoketo and J.-K. Kämäräinen), In Int. Conference on Computer Vision (ICCV) Workshops, 2019. [pdf]
  • Visibility-Aware Part Coding for Vehicle Viewing Angle Estimation (D. Yang, Ke Chen, D. Cai, S. Yang and J.-K. Kämäräinen), In 9th Int. Conf. on Information Society and Technology, 2019.
  • Cross-Granularity Attention Network for Semantic Segmentation (L. Zhu, T. Wang, E. Aksu and J.-K. Kämäräinen), In Int. Conf. Computer Vision (ICCV) Workshops, 2019. [pdf]

2018

  • Keyframe-Based Video Sumarization with Human in the Loop (A.E. Ainasoja, A. Hietanen, J. Lankinen and J.-K. Kämäräinen), In Int. Conf. on Computer Vision Theory and Applications (VISAPP), 2018. [pdf]
  • Convolutional Low-Resolution Fine-Grained Classification (D. Cai, K. Chen, Y. Qian and J.-K. Kämäräinen), In Pattern Recognition Letters, 2018. [pdf] [doi]
  • ADVIO: An authentic dataset for visual-inertial odometry. (Cortes S., Solin A., Rahtu E. and Kannala J.), In European Conference on Computer Vision (ECCV), 2018.
  • 360 Panorama Super-Resolution Using Deep Convolutional Networks (V. Fakour-Sevom, E. Guldogan and J.-K. Kämäräinen), In Int. Conf. on Computer Vision Theory and Applications (VISAPP), 2018. [pdf]
  • Review of vision-based safety systems for human-robot collaboration (R.-J. Halme, M. Lanz, J.-K. Kämäräinen, R. Pieters, J. Latokartano and A. Hietanen), In Procedia CIRP – 51st CIRP Conf. on Manufacturing Systems, 2018. [doi]
  • Depth-sensor-projector safety model for human-robot collaboration (A. Hietanen, R.-J. Halme, J. Latokartano, R. Pieters, M. Lanz and J.-K. Kämäräinen), In IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS) Workshops, 2018. [pdf]
  • How to Make an RGBD Tracker? (U. Kart, J.-K. Kämäräinen and J. Matas), In European Conference on Computer Vision (ECCV) Workshops, 2018. [pdf] [code]
  • Depth Masked Discriminative Correlation Filter (U. Kart, J.-K. Kämäräinen, J. Matas, L. Fan and F. Cricri), In Int. Conf. on Pattern Recognition (ICPR), 2018. (Nominee for the Best Industry Related Paper Award) [pdf]
  • Evaluation of Visual Object Trackers on Equirectangular Panorama (U. Kart, J.-K. Kämäräinen, L. Fan and M. Gabbouj), In Int. Conf. on Computer Vision Theory and Applications (VISAPP), 2018. [pdf]
  • Real-time human pose estimation with convolutional neural networks. (Linna M., Rahtu E. and Kannala J.), In International Conference on Computer Vision Theory and Applications (VISAPP), 2018.
  • Cascade of Boolean detector combinations (K. Mahkonen, T. Virtanen and J.-K. Kämäräinen), In EURASIP Journal on Image and Video Processing, volume 61, 2018. [doi]
  • Efficient and Robust Methods for Audio and Video Signal Analysis (K. Mahkonen), PhD thesis, Tampere University of Technology, 2018. [url]
  • Automated video face labelling for films and TV material. (Parkhi O., Rahtu E., Cao Q. and Zisserman A.), In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), volume , 2018. [doi]
  • Focus model for metric depth estimation in standard plenoptic cameras (S. Pertuz, E. Pulido-Herrera and J.-K. Kämäräinen), In ISPRS Journal of Photogrammetry and Remote Sensing, volume 144, 2018. [pdf] [doi] [code]
  • Hierarchical Deformable Part Models for Heads and Tails (F. Shokrollahi Yancheshmeh, K. Chen and J.-K. Kämäräinen), In Int. Conf. on Computer Vision Theory and Applications (VISAPP), 2018. [pdf]
  • Inertial Odometry on Handheld Smartphones. (Solin A., Cortes S., Rahtu E. and Kannala J.), In International Conference on Information Fusion (FUSION), 2018.
  • PIVO: Probabilistic Inertial-Visual Odometry for occlusion-robust navigation. (Solin A., Cortes S., Rahtu E. and Kannala J.), In IEEE Winter Conference on Applications of Computer Vision (WACV), 2018.
  • Bottom-up attention guidance for recurrent image recognition. (Tavakoli H., Borji A., Anwer R., Rahtu E. and Kannala J.), In IEEE International Conference on Image Processing (ICIP), 2018.
  • Summarization of user-generated sports video by using deep action recognition features. (Tejero-de-Pablos A., Nakashima Y., Sato T., Yokoya N., Linna M. and Rahtu E.), In IEEE Transactions on Multimedia, volume 20, 2018. [doi]
  • Automatic Knee Osteoarthritis Diagnosis from Plain Radiographs: A Deep Learning-Based Approach. (Tiulpin A., Thevenot J., Rahtu E., Lehenkari P. and Saarakkala S.), In Scientific reports, volume 8, 2018.
  • Learning image-to-image translation using paired and unpaired training samples. (Tripathy S., Kannala J. and Rahtu E.), In Asian Conference on Computer Vision (ACCV), 2018.
  • Object Detection in Equirectangular Panorama (W. Yang, Y. Qian, F. Cricri, L. Fan and J.-K. Kämäräinen), In Int. Conf. on Pattern Recognition (ICPR), 2018. [pdf] [code]

2017

  • Urban 3D Segmentation and Modelling From Street View Images and LiDAR Point Clouds (P. Babahajiani, L. Fan, J.-K. Kämäräinen and M. Gabbouj), In Machine Vision and Applications, volume 28, 2017. [url] [doi]
  • Estimation of Flow Turbulence Metrics With a Lateral Line Probe and Regression (K. Chen, J.A. Tuhtan, J.F. Fuentes-Pérez, G. Toming, M. Musall, N. Strokina, J.-K. Kämäräinen and M. Kruusmaa), In IEEE Transactions on Instrumentation and Measurements, volume 66, 2017. [pdf] [doi]
  • Spectral Attribute Learning for Visual Regression (K. Chen, K. Jia, Z. Zhang and J.-K. Kämäräinen), In Pattern Recognition, volume 66, 2017. [pdf] [doi]
  • Robustifying Correspondence Based 6D Object Pose Estimation (A. Hietanen, J. Halme, A. Glent Buch, J. Latokartano and J.-K. Kämäräinen), In IEEE Int. Conf. on Robotics and Automation (ICRA), 2017. [pdf]
  • Universal Robotics -käsivarren ohjaus Kinectillä (Samuli Koivisto), Technical report, Tampere University of Signal Processing, 2017. [pdf] [code]
  • Image-based Localization using Hourglass Networks. (Melekhov I., Ylioinas J., Kannala J. and Rahtu E.), In Geometry Meets Deep Learning ICCV Workshop (ICCVW), 2017.
  • Relative camera pose estimation using convolutional neural networks. (Melekhov I., Ylioinas J., Kannala J. and Rahtu E.), In International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS), 2017.
  • Fine-grained video retrieval for multi-clip video. (Otani M., Nakashima Y., Rahtu E. and Heikkilä J.), In Closing the Loop Between Vision and Language ICCV Workshop (ICCV-CLVL), 2017.
  • Region-based Depth Recovery for Highly Sparse Depth Maps (S. Pertuz and J.-K. Kämäräinen), In Int. Conf. on Image Processing (ICIP2017), 2017. [pdf]
  • Recurrent Color Constancy (Y. Qian, K. Chen, J. Nikkanen, J.-K. Kämäräinen and J. Matas), In Int. Conf. on Computer Vision (ICCV), 2017. [pdf] [code]
  • The World of Fast Moving Objects (D. Rozumnyi, J. Kotera, F. Sroubek, L. Novotny and J. Matas), In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2017. [pdf]
  • Improvement of Deep Learning Models on Classification Tasks Using Haar Transform and Model Ensemble (Nguyen Son Tung), Technical report, Häme University of Applied Sciences, 2017. [pdf]
  • Exploiting inter-image similarity and ensemble of extreme learners for fixation prediction using deep features. (Tavakoli H., Borji A., Laaksonen J. and Rahtu E.), In Neurocomputing, volume 244, 2017.
  • Video event classification using 3D convolutional neural networks (Iikka Teivas), Master’s thesis, Tampere University of Technology, 2017. [url]
  • A novel method for automatic localization of joint area on knee plain rediographs. (Tiulpin A., Thevenot J., Rahtu E. and Saarakkala S.), In Scandinavian Conference on Image Analysis (SCIA), 2017.
  • Cross-granularity graph inference for semantic video object segmentation (H. Wang, T. Wang, K. Chen and J.-K. Kämäräinen), In Int. Joint Conf. on Artificial Intelligence (IJCAI), 2017. [pdf]
  • Hierarchical regression learning for car pose estimation (Dan Yang), Master’s thesis, University of Tampere, 2017. [url]
  • Hierarchical Sliding Slice Regression for Vehicle Viewing Angle Estimation (D. Yang, K. Chen, Y. Qian, E. Berki and J.-K. Kämäräinen), In IEEE Transactions on Intelligent Transportation Systems, 2017. [pdf] [doi]
  • Dominant Convolutional Feature Channels for Image Subcategory Clustering (Peng Yao), Master’s thesis, Tampere University of Technology, 2017. [url]
  • Identity-aware Convolutional Neural Networks for Facial Expression Recognition (C. Zhang, P. Wang K. Chen and J.-K. Kämäräinen), In Journal of Systems Engineering and Electronics, volume 28, 2017. [pdf] [doi]

2016

  • Video Summarization with Key Frames (Antti Ainasoja), Master’s thesis, Tampere University of Technology, 2016.
  • Comprehensive Automated 3D Urban Environment Modelling Using Terrestrial Laser Scanning Point Cloud (P. Babahajiani, L. Fan, J.-K. Kämäräinen and M. Gabbouj), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2016. [pdf]
  • Learning with Ambiguous Label Distribution for Apparent Age Estimation (K. Chen and J.-K. Kämäräinen), In Asian Conference on Computer Vision (ACCV), 2016. [pdf]
  • Facial Age Estimation Using Robust Label Distribution (K. Chen, Z. Zhang and J.-K. Kämäräinen), In ACM Multimedia Conference (ACMMM), 2016. [pdf]
  • Pedestrian Density Analysis in Public Scenes with Spatio-Temporal Tensor Features (K. Chen and J.-K. Kämäräinen), In IEEE Transactions on Intelligent Transportation Systems, volume 17, 2016. [pdf] [doi]
  • Visualizing retinal vessel dynamics of young type 1 diabetic patients using self-organizing map (S. Haikonen, J. Kytö, J.-K. Kämäräinen, J.P. Kauppi, H. Huttunen, P.H. Groop and P. Summanen), In Acta Ophthalmologica, volume 94, 2016. [doi]
  • Measurement data processing. (Janne H., Rahtu E., Särkkä S., Kannala J., Solin A. and Tolvanen V.), 2016.
  • A Comparison of Feature Detectors and Descriptors for Object Class Matching (A. Hietanen, J. Lankinen, A.G. Buch, J.-K. Kämäräinen and N. Küger), In Neurocomputing, volume 184, 2016. [pdf] [doi] [code]
  • Car Type Recognition with Deep Neural Networks (H. Huttunen, F. Shokrollahi Yancheshmeh and Ke Chen), In IEEE Intelligent Vehicles Symposium, 2016.
  • On the contribution of saliency in visual tracking. (Iman A., Tavakoli H., Rahtu E. and Laaksonen J.), In International Conference on Computer Vision Theory and Applications (VISAPP), 2016.
  • Robust loop closures for scene reconstruction by combining odometry and visual correspondences. (Laskar Z., Huttunen S., Herrera Castro D., Rahtu E. and Kannala J.), In IEEE International Conference on Image Processing (ICIP), 2016.
  • Incremental Convolutional Neural Network Training (Y. Liu, Y. Qian, K. Chen, J.-K. Kämäräinen, H. Huttunen, L. Fan and J. Saarinen), In International Conference on Pattern Recognition (ICPR) Workshops, 2016. [pdf] [code]
  • Cascade processing for speeding up sliding window sparse classification (K. Mahkonen, A. Hurmalainen, T. Virtanen and J.-K. Kämäräinen), In European Signal Processing Conference (EUSIPCO), 2016. [pdf]
  • Siamese network features for image matching. (Melekhov I., Kannala J. and Rahtu E.), In International Conference on Pattern Recognition (ICPR), 2016.
  • Image patch matching using convolutional descriptors with Euclidean distance. (Melekhov I., Kannala J. and Rahtu E.), In Interpretation and Visualization of Deep Neural Nets ACCV Workshop, 2016.
  • Video summarization using deep semantic features. (Otani M., Nakashima Y., Rahtu E., Heikkilä J. and Yokoa N.), In Asian Conference on Computer Vision (ACCV), 2016.
  • Learning joint representations of videos and sentences with web image search. (Otani M., Nakashima Y., Rahtu E., Heikkilä J. and Yokoa N.), In Web-scale Vision and Social Media ECCV Workshop (ECCV-WS), 2016.
  • Dense 3D Models From a Single RGB-D View (Antti Pohjola), Master’s thesis, Tampere University of Technology, 2016. [pdf]
  • Deep Structured-Output Regression Learning for Computational Color Constancy (Y. Qian, K. Chen, J.-K. Kämäräinen, J. Nikkanen and J. Matas), In 23rd Int. Conf. on Pattern Recognition (ICPR2016), 2016. [pdf]
  • Structured Deep Learning for Fine-grained Visual Classification (Yanlin Qian), Master’s thesis, Tampere University of Technology, 2016. [url]
  • Terrain navigation in the magnetic landscape: Particle filtering for indoor positioning. (Solin A., Särkkä S., Kannala J. and Rahtu E.), In European Navigation Conference (ECN), 2016.
  • Joint Estimation of bulk flow velocity and angle using a lateral line probe (N. Strokina, J.-K. Kämäräinen, J.A. Tuhtan, J.F. Fuentes-Pérez and M. Kruusmaa), In IEEE Transactions on Instrumentation and Measurements, volume 65, 2016. [pdf] [doi]
  • Design and application of a fish-shaped lateral line probe for flow measurement (J. Tuhtan, J.F. Fuentes-Perez, N. Strokina, G. Toming, M. Musall, M. Noack, J.-K. Kämäräinen and M. Kruusmaa), In Review of Scientific Instruments, volume 87, 2016. [doi]

2015

  • Automated Super-Voxel Based Features Classification of Urban Environments by Integrating 3D Point Cloud and Image Content (P. Babahajiani, L. Fan, J.-K. Kamarainen and M. Gabbouj), In IEEE Int. Conf. on Signal and Image Processing Applications, 2015. [pdf]
  • Progressive Visual Object Detection with Positive Training Examples Only (E. Riabchenko, K. Chen and J.-K. Kämäräinen), In Scandinavian Conf. on Image Analysis (SCIA2015), 2015. [pdf]
  • Visualizing Retinal Vessel Dynamics Using Self-Organizing Map (Satu Haikonen), Technical report, Tampere University of Signal Processing, 2015.
  • Magnetic positioning management. (Janne H., Rahtu E. and Kannala J.), 2015.
  • Positioning management. (Janne H. and Rahtu E.), 2015.
  • Computer Vision for Head Pose Estimation: Review of a Competition (H. Huttunen, K. Chen, A. Thakur, A. Krohn-Grimberghe, O. Gencoglu, X. Ni, M. Al-Musawi, L. Xu and H. Jacob van Veen), In Scandinavian Conf. on Image Analysis (SCIA2015), 2015. [pdf]
  • Local Features for Visual Object Class Matching and Video Scene Detection (A. Hietanen), Master’s thesis, Tampere University of Technology, 2015.
  • Online face recognition system based on local binary patterns and facial landmark tracking. (Linna M., Kannala J. and Rahtu E.), In Advanced Concepts for Intelligent Vision Systems (ACIVS), 2015.
  • Incremental Learning in Deep Neural Networks (Y. Liu), Master’s thesis, Tampere University of Technology, 2015.
  • Flow feature extraction for underwater robot localization: preliminary results (N. Muhammad, N. Strokina, G. Toming, J.A. Tuhtan, J.-K. Kämäräinen and M. Kruusmaa), In IEEE Int. Conf. on Robotics and Automation (ICRA), 2015. [pdf]
  • Generative Part-Based Gabor Object Detector (E. Riabchenko), PhD thesis, Lappeenranta University of Technology, 2015. [pdf]
  • Generative Part-Based Gabor Object Detector (E. Riabchenko and J.-K. Kämäräinen), In Pattern Recognition Letters, volume 68, 2015. [pdf] [code]
  • Kamerapohjainen paikannus (Ansse Saarimäki), Technical report, Tampere University of Signal Processing, 2015. [pdf]
  • Adaptive Kalman filtering and smoothing for gravitation tracking in mobile systems. (Särkkä S., Tolvanen V., Kannala J. and Rahtu E.), In Indoor Positioning and Navigation Conference (IPIN), 2015.
  • Unsupervised Visual Alignment with Similarity Graphs (F. Shokrollahi Yancheshmeh, K. Chen and J.-K. Kämäräinen), In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2015. [pdf] [code]
  • Analysis of sampling techniques for learning binarized statistical image features using fixations and salience. (Tavakoli H., Rahtu E. and Heikkilä J.), In European Conference on Computer Vision – workshop (ECCV-WS), 2015.
  • Hydrodynamic Classification of Natural Flows Using an Artificial Lateral Line and Frequency Domain Features (J.A. Tuhtan, N. Strokina, G. Toming, N. Muhammad, M. Kruusmaa and J.-K. Kämäräinen), In 36th IAHR World Congress, 2015.
  • Online measurement of the bubble size distribution in medium-consistency oxygen delignification. (H. Mutikainen, N. Strokina, T. Eerola, L. Lensu, H. Kälviäinen, and J. Käyhkö), In Appita Journal, volume 68, 2015.

2014

  • An O(n log n) cutting plane algorithm for structured output ranking. (Blaschko M B., Mittal A. and Rahtu E.), In German Conference on Pattern Recognition (GCPR), 2014.
  • Learning to Count with Back-Propagated Information (K. Chen and J.-K. Kämäräinen), In 22th Int. Conf. on Pattern Recognition (ICPR2014), 2014. [pdf]
  • Indoor Objects and Outdoor Urban Scenes Recognition by 3D Visual Primitives (J. Fu, J.-K. Kämäräinen, A. Glent Buch and N. Krüger), In Asian Conf. on Computer Vision (ACCV) Workshops, 2014. [pdf]
  • Simultaneous localization and mapping by using earth’s magnetic fields. (Janne H. and Rahtu E.), 2014.
  • A 3D Map Augmented Photo Gallery Application on Mobile Device (J. Fu, L. Fan, K. Roimela, Y. You and V. Mattila), In 21st Int. Conf. on Image Processing (ICIP2014), 2014. [pdf]
  • Guest Editorial: Best of 18th Scandinavian Conference On Image Analysis 2013 (J.-K. Kämäräinen and M. Koskela), In Pattern Recognition Letters, volume 49, 2014.
  • Local Features in Image and Video Processing – Object Class Matching and Video Shot Detection (J. Lankinen), PhD thesis, Lappeenranta University of Technology, 2014. [pdf]
  • A malaria diagnostic tool based on computer vision screening and visualization of plasmodium falciparum candidate areas in digitized blood smears. (Linder N., Turkki R., Walliander M., Märtenson A., DiwanV., Rahtu E., Pietikäinen M., Lundin M. and Lundin M.), In PLoS ONE, volume 9, 2014.
  • Lifelog Scene Change Detection Using Cascades of Audio and Video Detectors (K. Mahkonen, J.-K. Kämäräinen and T. Virtanen), In Asian Conf. on Computer Vision (ACCV) Workshops, 2014. [pdf]
  • Generating object segmentation proposals using global and local search. (Rantalankila P., Kannala J. and Rahtu E.), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014.
  • Background calibration. (Rantalankila P., Rahtu E. and Kannala J.), 2014.
  • Density-Aware Part-Based Object Detection with Positive Examples (E. Riabchenko, J.-K. Kämäräinen and K. Chen), In 22th Int. Conf. on Pattern Recognition (ICPR2014), 2014. [pdf]
  • Learning Generative Models of Object Parts from A Few Positive Examples (E. Riabchenko, J.-K. Kämäräinen and K. Chen), In 22th Int. Conf. on Pattern Recognition (ICPR2014), 2014. [pdf]
  • Unsupervised Alignment of Objects in Images (Fatemeh Shokrollahi Yancheshmeh), Master’s thesis, Tampere University of Technology (TUT), 2014. [pdf]
  • Discovering Multi-Relational Latent Attributes by Visual Similarity Networks (F. Shokrollahi Yancheshmeh, J.-K. Kämäräinen and K. Chen), In Asian Conf. on Computer Vision (ACCV) Workshops, 2014. [pdf]
  • Total Cluster: A person agnostic clustering method for broadcast videos. (Tapaswi M., Parkhi O., Rahtu E., Sommerlade E., Stiefelhagen R. and Zisserman A.), In Indian Conference on Computer Vision (ICVGIP), 2014.
  • Analysis of sampling techniques for learning binarized statistical image features using fixations and salience. (Tavakoli H., Rahtu E. and Heikkilä J.), In ECCV 2014 Second International Workshop of Computer Vision With Local Binary Patterns Variants, 2014.
  • Emotional valence recognition, analysis of salience and eye movements. (Tavakoli H., Yanulevskaya V., Rahtu E., Heikkilä J. and Sebe N.), In International Conference on Pattern Recognition (ICPR), 2014.
  • Live RGB-D Camera Tracking for Television Production Studios (T. Tykkälä, A.I. Comport, J.-K. Kämäräinen and H. Hartikainen), In Journal of Visual Communication and Image Representation, volume 25, 2014. [pdf] [code]
  • Understanding objects in detail with fine-grained attributes. (Vedaldi A., Mahendran S., Tsogkas S., Maji S., Girshick R., Kannala J., Rahtu E., Kokkinos I., Blaschko M B., Weiss D., Taskar B., Simonyan K., Saphra N. and Mohammed S.), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014.
  • Image-based characterization of the pulp flows. (M. Sorokin, N. Strokina, T. Eerola, L. Lensu, and H. Kälviäinen), In the 9th Open German-Russian Workshop on Pattern Recognition and Image Understanding (OGRW 2014), 2014.
  • Comparison of appearance-based and geometry-based bubble detectors (Strokina, N., Juranek, R., Eerola, T., Lensu, L., Zemcik, P. and H. Kälviäinen), In International Conference on Computer Vision and Graphics (ICCVG), 2014. [url]

2013

  • Non maximal suppression in cascaded ranking models. (Blaschko M B., Kannala J. and Rahtu.), In Scandinavian Conference on Image Analysis (SCIA), 2013.
  • Pose Estimation Using Local Structure-Specific Shape and Appearance Context (A.G. Buch, D. Kraft, J.-K. Kamarainen, H.G. Petersen and N. Krüger), In IEEE Int. Conf. on Robotics and Automation (ICRA), 2013. [pdf]
  • Pose Estimation Using a Hierarchical 3D Representation of Contours and Surfaces (A.G. Buch, D. Kraft, J.-K. Kämäräinen and N. Krüger), In Int. Conf. on Computer Vision Theory and Applications (VISAPP), 2013. [pdf]
  • Automatic dynamic texture segmentation using local descriptors and optical flow. (Chen J., Zhao G., Salo M., Rahtu E. and Pietikäinen M.), In IEEE transactions on Image Processing (TIP), volume 22, 2013.
  • Local phase quantization for blur insensitive texture description. (Heikkilä J., Rahtu E. and Ojansivu V.), Chapter in Local Binary Patterns: New Variants and Application, Springer, 2013.
  • Constructing Benchmark Databases and Protocols for Medical Image Analysis: Diabetic Retinopathy (Tomi Kauppi, J.-K. Kämäräinen, Lasse Lensu, Valentina Kalesnykiene, Iiris Sorri, Hannu Uusitalo and Heikki Kälviäinen), In Computational and Mathematical Methods in Medicine, volume 2013, 2013. [url]
  • Unsupervised visual object categorisation with BoF and spatial matching (T. Kinnunen, J. Lankinen, J.-K. Kämäräinen, L. Lensu and H. Kälviäinen), In Scandinavian Conf. on Image Analysis (SCIA2013), 2013. [pdf]
  • Video Shot Boundary Detection Using Visual Bag-of-Words (J. Lankinen and J.-K. Kämäräinen), In Int. Conf. on Computer Vision Theory and Applications (VISAPP), 2013. [pdf]
  • Supervised Object Class Colour Normalisation (E. Riabchenko, J. Lankinen, A.G. Buch, J.-K. Kämäräinen and N. Krueger), In Scandinavian Conf. on Image Analysis (SCIA2013), 2013. [pdf]
  • Stochastic bottom-up fixation prediction and saccade generation. (Tavakoli H., Rahtu E. and Heikkilä J.), In Image and Vision Computing (IVC), volume 31, 2013.
  • Temporal saliency for fast background subtraction. (Tavakoli H., Rahtu E. and Heikkilä J.), In Asian Conference on Computer Vision (ACCV) workshops, Part I (BMC), LNCS 7728, 2013.
  • Saliency detection using joint temporal and spatial decorrelation. (Tavakoli H., Rahtu E. and Heikkilä J.), In Scandinavian Conference on Image Analysis (SCIA), 2013.
  • Real-Time Image-Based RGB-D Camera Motion Tracking and Environment Mapping (T.M. Tykkälä), PhD thesis, Lappeenranta University of Technology, 2013. [pdf] [code]
  • Photorealistic 3D Mapping of Indoors by RGB-D Scanning Process (T. Tykkälä, A.I. Comport and J.-K. Kämäräinen), In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2013. [pdf]
  • RGB-D Tracking and Reconstruction for TV Broadcasts (T. Tykkälä, H. Hartikainen, A.I. Comport and J.-K. Kämäräinen), In Int. Conf. on Computer Vision Theory and Applications (VISAPP), 2013. [pdf]
  • 18th Scandinavian Conf. on Image Analysis, (J.-K. Kämäräinen, M. Koskela, eds.), Springer, 2013. [url]

2012

  • Discriminative co-segmentation method for image classification. (Chai Y., Rahtu E., Zisserman A., Lempitsky V. and Van Gool L.), In European Conference on Computer Vision (ECCV), 2012.
  • From Full-Reference to No-Reference in Quality Assessment of Printed Images (T. Eerola, J.-K. Kamarainen, L. Lensu and H. Kälviäinen), In Federated Computer Science Event, 2012. [pdf]
  • Gabor Features in Image Analysis (J.-K. Kamarainen), In Int. Conf. on Image Processing Theory, Tools and Applications (IPTA2012), 2012. [pdf]
  • Combining Multiple Image Segmentations by Maximizing Expert Agreement (J.-K. Kamarainen, L. Lensu and T. Kauppi), In Int. Conf. on Medical Image Computing and Computer Assisted Intervention (MICCAI) Workshops, 2012. [pdf]
  • A Framework for Constructing Benchmark Databases and Protocols for Retinopathy in Medical Image Analysis (T. Kauppi, J.-K. Kamarainen, L. Lensu, V. Kalesnykiene, I. Sorri, H. Uusitalo and H. Kälviäinen), In Workshop on Intelligence Science and Intelligent Data Engineering (IScIDE), 2012. [pdf]
  • Unsupervised Object Discovery via Self-Organisation (T. Kinnunen, J.-K. Kamarainen, L. Lensu and H. Kälviäinen), In Pattern Recognition Letters, volume 33, 2012. [pdf]
  • Visual Saliency and Categorisation of Abstract Images (M. Laine-Hernandez, T. Kinnunen, J.-K. Kamarainen, L. Lensu, H. Kälviäinen and P. Oittinen), In 21th Int. Conf. on Pattern Recognition (ICPR2012), 2012. [pdf]
  • A comparison of local feature detectors and descriptors for visual object categorization by intra-class repeatability and matching (J. Lankinen, V. Kangas and J.-K. Kamarainen), In 21th Int. Conf. on Pattern Recognition (ICPR2012), 2012. [pdf]
  • Identification of tumor epithelium and stroma in tissue microarrays using texture analysis. (Linder N., Konsti J., Turkki R., Rahtu E., Lundin M., Nordling S., Ahonen T., Pietikäinen M. and Lundin J.), In Diagnostic Pathology, volume 7, 2012.
  • Local phase quantization for blur-insensitive image analysis. (Rahtu E., Heikkilä J., Ojansivu V. and Ahonen T.), In Image and Vision Computing (IVC), volume 30, 2012.
  • BSIF: binarized statistical image features. (Rahtu E and Kannala J.), In International Conference on Pattern Recognition (ICPR), 2012.
  • Federated Computer Science Event, (S. Tarkoma, J.-K. Kamarainen, T. Pahikkala, eds.), Unigrafia, 2012. [pdf]

2011

  • Thresholding based detection of fine and sparse details (A. Drobchenko, J.-K. Kamarainen, L. Lensu, J. Vartiainen, H. Kälviäinen and T. Eerola), In Frontiers of Electrical and Electronic Engineering in China, volume 6, 2011.
  • Bayesian network model of overall print quality: construction and structural optimisation (T. Eerola, L. Lensu, J.-K. Kamarainen, T. Leisti, R. Ritala, G. Nyman and H. Kälviäinen), In Pattern Recognition Letters, volume 32, 2011. [pdf]
  • Real-time detection of landscape scenes. (Huttunen S., Rahtu E., Kunttu I., Gren J. and Heikkilä J.), In Scandinavian Conference on Image Analysis (SCIA), 2011.
  • Facial Feature Representation (J.-K. Kamarainen, A. Hadid and M. Pietikäinen), Chapter in Handbook of Face Recognition, Springer, 2011. [url]
  • Local Feature Based Unsupervised Alignment of Object Class Images (J. Lankinen and J.-K. Kamarainen), In British Machine Vision Conference (BMVC2011), 2011. [pdf]
  • Projector calibration by “inverse camera calibration” (I. Martynov, J.-K. Kamarainen and L. Lensu), In Scandinavian Conf. on Image Analysis (SCIA2011), 2011. [pdf]
  • Volume local phase quantization for blur-insensitive dynamic texture classification. (Päivärinta J., Rahtu E. and Heikkilä J.), In Scandinavian Conference on Image Analysis (SCIA), 2011.
  • Segmentation based watermark recovery from a dual layer hologram with a digital camera. (Pramila A., Keskinarkaus A., Rahtu E. and Seppänen T.), In Scandinavian Conference on Image Analysis (SCIA), 2011.
  • Learning a Category Independent Object Detection Cascade. (Rahtu E., Kannala J. and Blaschko M B.), In IEEE International Conference on Computer Vision (ICCV), 2011.
  • Fast and efficient saliency detection using sparse sampling and kernel density estimation. (Tavakoli H., Rahtu E. and Heikkilä J.), In Scandinavian Conference on Image Analysis (SCIA), 2011.

2010

  • Full Reference Printed Image Quality: Measurement Framework and Statistical Evaluation (T. Eerola, J.-K. Kamarainen, L. Lensu, T. Leisti, R. Halonen, H. Kälviäinen, G. Nyman and P. Oittinen), In Journal of Imaging Science and Technology (JIST), volume 54, 2010. (Charles E. Ives Journal Award for the best paper) [pdf]
  • The structural form in image categorization. (Hanni J., Rahtu E. and Ojansivu V.), In International Conference on Computer Vision Theory and Applications (VISAPP), 2010.
  • Improved blur insensitivity for decorrelated local phase quantization. (Heikkilä J., Rahtu E. and Ojansivu V.), In International Conference on Pattern Recognition (ICPR), 2010.
  • Learning and Detection of Object Landmarks in Canonical Object Space (J.-K. Kamarainen and J. Ilonen), In 20th Int. Conf. on Pattern Recognition (ICPR2010), 2010. [pdf]
  • Unsupervised Visual Object Categorisation via Self-Organisation (T. Kinnunen, J.-K. Kamarainen, L. Lensu and H. Kälviäinen), In 20th Int. Conf. on Pattern Recognition (ICPR2010), 2010. [pdf]
  • Making Visual Object Categorization More Challenging: Randomized Caltech-101 Data Set (T. Kinnunen, J.-K. Kamarainen, L. Lensu, J. Lankinen and H. Kälviäinen), In 20th Int. Conf. on Pattern Recognition (ICPR2010), 2010. [pdf]
  • Narrow Baseline GLSL Multiview Stereo (P. Paalanen and J.-K. Kamarainen), In 3D Data Processing, Visualization and Transmission (3DPVT), 2010. [pdf] [code]
  • Segmenting salient objects from images and videos. (Rahtu E., Kannala J., Salo M. and Heikkilä J.), In European Conference on Computer Vision (ECCV), 2010.
  • Compressing sparse feature vectors using random ortho-projections. (Rahtu E., Salo M. and Heikkilä J.), In International Conference on Pattern Recognition (ICPR), 2010.

2009

  • Framework for Applying Full Reference Digital Image Quality Measures to Printed Images (T. Eerola, J.-K. Kamarainen, L. Lensu and H. Kälviäinen), In Scandinavian Conf. on Image Analysis (SCIA2009), 2009.
  • Experimental Study on Fast 2D Homography Estimation from a Few Point Correspondences (J.-K. Kamarainen and P. Paalanen), Technical report 111, Department of Information Technology, Lappeenranta University of Technology, 2009. [pdf] [code]
  • Dense and deformable motion segmentation for wide baseline images. (Kannala J., Rahtu E., Brand SS. and Heikkilä J.), In Scandinavian Conference on Image Analysis (SCIA), 2009.
  • Fusion of multiple expert annotations and overall score selection for medical image diagnosis (T. Kauppi, J.-K. Kamarainen, L. Lensu, V. Kalesnykiene, I. Sorri, H. Kälviäinen, H. Uusitalo and J. Pietilä), In Scandinavian Conf. on Image Analysis (SCIA2009), 2009. [pdf]
  • The role of model-based illumination correction in processing colour eye fundus images (T. Kauppi, L. Lensu, J.-K. Kamarainen, P. Fält, M. Hauta-Kasari, J. Hiltunen, V. Kalesnykiene, I. Sorri, H. Uusitalo, H. Kälviäinen and J. Pietilä), In Medical Physics and Biomedical Engineering World Congress (WC2009), 2009.
  • Bag-of-Features Codebook Generation by Self-Organisation (T. Kinnunen, J.-K. Kamarainen, L. Lensu and H. Kälviäinen), In 7th Int. Workshop on Self-Organizing Maps (WSOM2009), 2009.
  • Image Based Quantitative Mosaic Evaluation with Artificial Video (P. Paalanen, J.-K. Kamarainen and H. Kälviäinen), In Scandinavian Conf. on Image Analysis (SCIA2009), 2009. [pdf] [code]
  • A simple and efficient saliency detector for background subtraction. (Rahtu E and Heikkilä J.), In Workshop on Visual Surveillance (ICCV-VS), 2009.
  • Affine invariant features in pattern recognition. (Rahtu E. and Heikkilä J.), Chapter in Handbook of Pattern Recognition and Computer Vision, World Scientific, 2009.
  • Applying visual object categorization and memory colors for automatic color constancy. (Rahtu E., Nikkanen J., Kannala J., Lepistö L. and Heikkilä J.), In International Conference on Image Analysis and Processing (ICIAP), 2009.

2008

  • Recognition of blurred faces using local phase quantization. (Ahonen T., Rahtu E., Ojansivu V. and Heikkilä J.), In International Conference on Pattern Recognition (ICPR), 2008.
  • Finding best measurable quantities for predicting human visual quality experience (T. Eerola, J.-K. Kamarainen, T. Leisti, R. Halonen, L. Lensu, H. Kälviäinen, P. Oittinen and G. Nyman), In IEEE Int. Conf. on Systems, Man and Cybernetics, 2008.
  • Is there hope for predicting human visual quality experience? (T. Eerola, J.-K. Kamarainen, T. Leisti, R. Halonen, L. Lensu, H. Kälviäinen, G. Nyman and P. Oittinen), In IEEE Int. Conf. on Systems, Man and Cybernetics, 2008.
  • Image feature localization by multiple hypothesis testing of Gabor features (J. Ilonen, J.-K. Kamarainen, P. Paalanen, M. Hamouz, J. Kittler and H. Kälviäinen), In IEEE Transactions on Image Processing, volume 17, 2008. [pdf]
  • Object recognition and segmentation by non-rigid quasi-dense matching. (Kannala J., Rahtu E., Brandt S. and Heikkilä J.), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008.
  • Rotation invariant blur insensitive texture analysis using local phase quantization. (Ojansivu V., Rahtu E and Heikkilä J.), In International Conference on Pattern Recognition (ICPR), 2008.
  • Towards online 3D reconstruction (P. Paalanen, V. Kyrki and J.-K. Kamarainen), In European Conference on Computer Vision (ECCV) Workshops, 2008. [pdf]
  • Detection of irregularities in regular patterns (J. Vartiainen, A. Sadovnikov, J.-K. Kamarainen, L. Lensu and H. Kälviäinen), In Machine Vision and Applications, volume 19, 2008. [pdf]

2007

  • Object class detection using local image features and point pattern matching constellation search (A. Drobchenko, J. Ilonen, J.-K. Kamarainen, A. Sadovnikov, H. Kälviäinen and M. Hamouz), In Scandinavian Conf. on Image Analysis (SCIA2007), 2007.
  • Visual Print Quality Evaluation Using Computational Features (T. Eerola, J.-K. Kamarainen, L. Lensu and H. Kälviäinen), In 3rd Int. Symposium on Visual Computing, 2007.
  • Fast extraction of multi-resolution Gabor features (J. Ilonen, J.-K. Kamarainen and H. Kälviäinen), In 14th International Conference on Image Analysis and Processing, 2007.
  • Object Localisation Using Generative Probability Model for Spatial Constellation and Local Image Features (J.-K. Kamarainen, M. Hamouz, J. Kittler, P. Paalanen, J. Ilonen and A. Drobchenko), In International Conference on Computer Vision (ICCV) Workshops, 2007. [pdf]
  • Local and Global Gabor Features for Object Recognition (J.-K. Kamarainen, V. Kyrki and H. Kälviäinen), In Pattern Recognition and Image Analysis, volume 17, 2007.
  • The DIARETDB1 diabetic retinopathy database and evaluation protocol (T. Kauppi, V. Kalesnykiene, J.-K. Kamarainen, L. Lensu, I. Sorri, A. Raninen, A., R. Voutilainen, H. Uusitalo, H. Kälviäinen and J. Pietilä), In British Machine Vision Conference (BMVC2007), volume 1, 2007. [pdf]
  • DIARETDB1 diabetic retinopathy database and evaluation protocol (T. Kauppi, V. Kalesnykiene, J.-K. Kamarainen, L. Lensu, I. Sorri, A. Raninen, R. Voutilainen, J. Pietilä, H. Kälviäinen and H. Uusitalo), In Medical Image Understanding and Analysis (MIUA2007), 2007.
  • Asiantuntijatiedon käyttö silmänpohjakuvien automaattisessa tulkinnassa (T. Kauppi, V. Kalesnykiene, L. Lensu, J.-K. Kamarainen, I. Sorri, A. Raninen, R. Voutilainen, H. Kälviäinen, J. Pietilä and H. Uusitalo), In , 2007.
  • Goniometric Imaging of Paper Gloss (T. Kauppi, A. Sadovnikov, L. Lensu, J.-K. Kamarainen, P. Silfsten and H. Kälviäinen), In IAPR Conf. on Machine Vision Applications, 2007.
  • Image Based Quantitative Mosaic Evaluation with Artificial Video (P. Paalanen, J.-K. Kamarainen and H. Kälviäinen), Technical report 106, Department of Information Technology, Lappeenranta University of Technology, 2007.
  • Real-Time On-Screen Mosaic Rendering (P. Paalanen, J.-K. Kamarainen, L. Lensu, V. Kyrki and H. Kälviäinen), In Finnish Signal Processing Symposium, 2007.
  • Nonlinear functionals in the construction of affine invariants. (Rahtu E., Salo M. and Heikkilä J.), In Scandinavian Conference on Image Analysis (SCIA), 2007.
  • Affine registration using multiscale approach. (Rahtu E., Salo M. and Heikkilä J.), In Finnish Signal Processing Symposium (FINSIG), 2007.
  • A multiscale framework for affine invariant pattern recognition and registration. (Rahtu E.), 2007.

2006

  • Object categorization using self-organization over visual appearance (J. Ilonen and J.-K. Kamarainen), In Int. Joint Conf. on Neural Networks (IJCNN2006), 2006.
  • Toward Automatic Forecasts for Diffusion of Innovations (J. Ilonen, J.-K. Kamarainen, K. Puumalainen, S. Sundqvist and H. Kälviäinen), In Technological Forecasting & Social Change, volume 73, 2006. [pdf]
  • Gaussian mixture pdf in one-class classification: computing and utilizing confidence values (J. Ilonen, P. Paalanen, J.-K. Kamarainen and H. Kälviäinen), In 18th Int. Conf. on Pattern Recognition (ICPR), 2006. [pdf]
  • Invariance Properties of Gabor Filter Based Features – Overview and Applications (J.-K. Kamarainen, V. Kyrki and H. Kälviäinen), In IEEE Transactions on Image Processing, volume 15, 2006. [pdf]
  • Toward systemized collection of expert knowledge for fundus images in diabetic retinopathy (T. Kauppi, V. Kalesnykiene, L. Lensu, J.-K. Kamarainen, I. Sorri, H. Kälviäinen, J. Pietilä and H. Uusitalo), In Engineering the Eye II: Imaging the Retina, 2006.
  • Feature Representation and Discrimination Based on Gaussian Mixture Model Probability Densities – Practices and Algorithms (P. Paalanen, J.-K. Kamarainen, J. Ilonen and H. Kälviäinen), In Pattern Recognition, volume 39, 2006. [pdf] [code]
  • Generalized affine moment invariants for object recognition. (Rahtu E., Salo M., Heikkilä J. and Flusser J.), In International Conference on Pattern Recognition (ICPR), 2006.
  • Multiscale autoconvolution histograms for affine invariant pattern recognition. (Rahtu E., Salo M. and Heikkilä J.), In British Machine Vision Conference (BMVC), 2006.
  • A new affine invariant image transform based on ridgelets. (Rahtu E., Salo M. and Heikkilä J.), In British Machine Vision Conference (BMVC), 2006.
  • A new convexity measure based on a probabilistic interpretation of images. (Rahtu E., Salo M. and Heikkilä J.), In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), volume 28, 2006.
  • Model Based Generation of Random Stimuli and Parameter Analysis for Print Unevenness Evaluation (A. Sadovnikov, L. Lensu, J.-K. Kamarainen and H. Kälviäinen), In Proc. of the 29th European Conference on Visual Perception, 2006.
  • Measuring Translation Shiftability of Frames (J. Sampo, J.-K. Kamarainen, M. Heiliö and H. Kälviäinen), In Computers & Mathematics with Applications, volume 52, 2006.
  • Properties of patch based approaches for recognition of visual object classes. (Teynor A., Rahtu E., Lokesh S. and Burkhardt.), In German Conference on Pattern Recognition (DAGM), 2006.
  • Detecting irregularities in regular patterns (J. Vartiainen, L. Lensu, J.-K. Kamarainen, A. Sadovnikov and H. Kälviäinen), In 18th Int. Conf. on Pattern Recognition (ICPR2006), 2006.
  • Automating visual inspection of print quality (J. Vartiainen, S. Lyden, A. Sadovnikov, J.-K. Kamarainen, L. Lensu and H. Kälviäinen), In Int. Conf. on Image Analysis and Recognition, volume 2, 2006.
  • Minimum error contrast enhancement (J. Vartiainen, P. Paalanen, J.-K. Kamarainen, L. Lensu and H. Kälviäinen), Technical report 102, Department of Information Technology, Lappeenranta University of Technology, 2006.

2005

  • Thresholding Based Detection of Fine and Sparse Details (A. Drobchenko, J. Vartiainen, J.-K. Kamarainen, L. Lensu and H. Kälviäinen), Technical report 99, Department of Information Technology, Lappeenranta University of Technology, 2005.
  • Thresholding Based Detection of Fine and Sparse Details (A. Drobchenko, J. Vartiainen, J.-K. Kamarainen, L. Lensu and H. Kälviäinen), In IAPR Conf. on Machine Vision Applications, 2005. [pdf]
  • Automated Pattern Recognition for the Detection of Diabetic Changes in Digital Fundus Images (J. Forsstrom, V. Kalesnykiene, M. Kuivalainen, I. Sorri, H. Uusitalo and J.-K. Kamarainen), In ARVO 2005 Annual Meeting, 2005.
  • Feature-based affine-invariant localization of faces (M. Hamouz, J. Kittler, J.-K. Kamarainen, P. Paalanen, H. Kälviäinen and J. Matas), In IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), volume 27, 2005. [pdf]
  • Efficient computation of Gabor features (J. Ilonen, J.-K. Kamarainen and H. Kälviäinen), Technical report 100, Department of Information Technology, Lappeenranta University of Technology, 2005.
  • Diagnosis Tool for Motor Condition Monitoring (J. Ilonen, J.-K. Kamarainen, T. Lindh, J. Ahola, H. Kälviäinen and J. Partanen), In IEEE Transactions on Industry Applications, volume 41, 2005. [pdf]
  • Toward Automatic Motor Condition Diagnosis (J. Ilonen, P. Paalanen, J.-K. Kamarainen, T. Lindh, J. Ahola, H. Kälviäinen and J. Partanen), In 14th Scandinavian Conf. of Image Analysis (SCIA2005), 2005.
  • Intelligent Information Processing: Machine Vision and Pattern Recognition Applications (H. Kälviäinen and J.-K. Kamarainen), In Pattern Recognition and Image Analysis, volume 15, 2005.
  • Object Evidence Extraction Using Simple Gabor Features and Statistical Ranking (J.-K. Kamarainen, J. Ilonen, P. Paalanen, M. Hamouz, H. Kälviäinen and J. Kittler), In 14th Scandinavian Conf. of Image Analysis (SCIA2005), 2005.
  • Fundamental Frequency and Global Gabor Features (J.-K. Kamarainen, V. Kyrki and H. Kälviäinen), In Pattern Recognition and Image Analysis, volume 15, 2005.
  • A new method for affine registration of images and point sets. (Kannala J., Rahtu E., Heikkilä J. and Salo M.), In Scandinavian Conference on Image Analysis (SCIA), 2005.
  • Affine registration with multi-scale autoconvolution. (Kannala J., Rahtu E. and Heikkilä J.), In International Conference on Image Processing (ICIP), 2005.
  • Feature Representation and Discrimination Based on Gaussian Mixture Model Probability Densities – Practices and Algorithms (P. Paalanen, J.-K. Kamarainen, J. Ilonen and H. Kälviäinen), Technical report 95, Department of Information Technology, Lappeenranta University of Technology, 2005. [code]
  • Affine invariant pattern recognition using multiscale autoconvolution. (Rahtu E., Salo M. and Heikkilä J.), In IEEE transactions on pattern recognition and machine intelligence (TPAMI), volume 27, 2005.
  • A new efficient method for producing global affine invariants. (Rahtu E., Salo M. and Heikkilä J.), In International Conference on Image Analysis and Processing (ICIAP), 2005.
  • Quantified and Perceived Unevenness of Solid Printed Areas (A. Sadovnikov, L. Lensu, J.-K. Kamarainen and H. Kälviäinen), In 10th Iberoamerican Congress on Pattern Recognition, 2005.
  • Mottling Assessment of Solid Printed Areas and Its Correlation to Perceived Uniformity (A. Sadovnikov, P. Salmela, L. Lensu, J.-K. Kamarainen and H. Kälviäinen), In 14th Scandinavian Conf. of Image Analysis (SCIA2005), 2005.
  • Detection of irregularities in regular dot patterns (A. Sadovnikov, J. Vartiainen, J.-K. Kamarainen, L. Lensu and H. Kälviäinen), Technical report 93, Lappeenranta University of Technology, Department of Information Technology, 2005.
  • Detection of Irregularities in Regular Dot Patterns (A. Sadovnikov, J. Vartiainen, J.-K. Kamarainen, L. Lensu and H. Kälviäinen), In IAPR Conf. on Machine Vision Applications, 2005.

2004

  • Affine-Invariant Face Detection and Localization Using GMM-based Feature Detector and Enhanced Appearance Model (M. Hamouz, J. Kittler, J.-K. Kamarainen, P. Paalanen and H. Kälviäinen), In 6th Int. Conf. on Automatic Face and Gesture Recognition (FG2004), 2004.
  • Intelligent Information Processing: Machine Vision and Pattern Recognition Applications (H. Kälviäinen and J.-K. Kamarainen), In 7th Int. Conf. on Pattern Recognition and Image Analysis: New Information Technologies, volume 3, 2004.
  • PAPVISION: Paper and Board Printability Tests by Machine Vision in the Paper Making and Printing Industry (H. Kälviäinen, A. Sadovnikov, P. Salmela, A. Drobchenko, J.-K. Kamarainen, L. Lensu, P. Saarinen, P. and J. Vartiainen), In ECCV Workshop on Applications of Computer Vision, 2004.
  • Fundamental Frequency and Global Gabor Features (J.-K. Kamarainen, V. Kyrki and H. Kälviäinen), In 7th Int. Conf. on Pattern Recognition and Image Analysis: New Information Technologies, volume 1, 2004.
  • Simple Gabor Feature Space for Invariant Object Recognition (V. Kyrki, J.-K. Kamarainen and H. Kälviäinen), In Pattern Recognition Letters, volume 25, 2004. [pdf]
  • Object classification with multi-scale autoconvolution. (Rahtu E and Heikkilä J.), In International Conference on Pattern Recognition (ICPR), 2004.
  • Convexity recognition using multi-scale autoconvolution. (Rahtu E., Salo M. and Heikkilä J.), In International Conference on Pattern Recognition (ICPR), 2004.
  • Object recognition using multi-scale autoconvolution. (Rahtu E.), 2004.
  • Measuring Shiftability of Frames of Regular Translates (J. Sampo, J.-K. Kamarainen, M. Heiliö and H. Kälviäinen), In 6th Nordic Signal Processing Symposium, 2004.

2003

  • Hypotheses-driven affine invariant localization of faces in verification systems (M. Hamouz, J. Kittler, J.-K. Kamarainen and H. Kälviäinen), In 4th Int. Conf. on the Audio- and Video-Based Biometric Person Authentication (AVBPA2003), 2003.
  • Differential Evolution Training Algorithm for Feed-Forward Neural Networks (J. Ilonen, J.-K. Kamarainen and J. Lampinen), In Neural Processing Letters, volume 17, 2003. [pdf]
  • The Global Diffusion of Internet and Wireless Subscriptions: A Neural Network Approach (J. Ilonen, K. Puumalainen, S. Sundqvist, J.-K. Kamarainen and H. Kälviäinen), In , 2003.
  • Feature Extraction Using Gabor Filters (J.-K. Kamarainen), PhD thesis, Lappeenranta University of Technology, 2003. [pdf]
  • Improving Similarity Measures of Histograms Using Smoothing Projections (J.-K. Kamarainen, V. Kyrki and J. Ilonen), In Pattern Recognition Letters, volume 24, 2003. [pdf]
  • Statistical Signal Discrimination for Condition Diagnosis (J.-K. Kamarainen, V. Kyrki, T. Lindh, J. Ahola and J. Partanen), In Finnish Signal Processing Symposium, 2003.
  • Simple Gabor Feature Space for Invariant Object Recognition (V. Kyrki and J.-K. Kamarainen), In 5th Int. Conf. on Advanced Concepts for Intelligent Vision Systems Theory and Applications, 2003.
  • Simple Gabor Feature Space for Invariant Object Recognition (V. Kyrki and J.-K. Kamarainen), Technical report 83, Lappeenranta University of Technology, Department of Information Technology, 2003.
  • Bearing Damage Detection Based on Statistical Discrimination of Stator Current (T. Lindh, J. Ahola, J.-K. Kamarainen, V. Kyrki and J. Partanen), In 4th IEEE Int. Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, 2003.

2002

  • Automatic Detection and Recognition of Hazardous Chemical Agents (J. Ilonen, J.-K. Kamarainen, H. Kälviäinen and O. Anttalainen), In 14th Int. Conf. on Digital Signal Processing, volume 2, 2002. [url]
  • Fundamental Frequency Gabor Filters for Object Recognition (J.-K. Kamarainen, V. Kyrki and H. Kälviäinen), Technical report 78, Lappeenranta University of Technology, Department of Information Technology, 2002.
  • Gabor Features for Invariant Object Recognition (J.-K. Kamarainen, V. Kyrki and H. Kälviäinen), Technical report 79, Lappeenranta University of Technology, Department of Information Technology, 2002.
  • Fundamental Frequency Gabor Filters for Object Recognition (J.-K. Kamarainen, V. Kyrki and H. Kälviäinen), In 16th Int. Conf. on Pattern Recognition (ICPR2002), volume 1, 2002.
  • Noise Tolerant Object Recognition Using Gabor Filtering (J.-K. Kamarainen, V. Kyrki and H. Kälviäinen), In 14th Int. Conf. on Digital Signal Processing, volume 2, 2002.
  • Robustness of Gabor Feature Parameter Selection (J.-K. Kamarainen, V. Kyrki and H. Kälviäinen), In IAPR Workshop on Machine Vision Applications, 2002.
  • Invariant Gabor Features for Face Evidence Extraction (J.-K. Kamarainen, V. Kyrki, M. Hamouz, J. Kittler and H. Kälviäinen), In IAPR Workshop on Machine Vision Applications, 2002. [pdf]
  • Signal Discrimination Based on Power Spectrum of Filter Response (J.-K. Kamarainen, V. Kyrki and T. Lindh), Technical report 80, Lappeenranta University of Technology, Department of Information Technology, 2002.
  • Forecasting the Critical Mass of Wireless Communications (S. Sundqvist, L. Frank, K. Puumalainen, J.-K. Kamarainen and S. Pitkänen), In Australian and New Zealand Marketing Academy Conf., 2002.

2001

  • Similarity Measures for Ordered Histograms (J.-K. Kamarainen, V. Kyrki and H. Kälviäinen), In 12th Scandinavian Conf. on Image Analysis (SCIA2001), 2001.
  • Invariant Shape Recognition using Global Gabor Features (V. Kyrki, J.-K. Kamarainen and H. Kälviäinen), In 12th Scandinavian Conf. on Image Analysis (SCIA2001), 2001.
  • Content-Based Image Matching Using Gabor Filtering (V. Kyrki, J.-K. Kamarainen and H. Kälviäinen), In 3rd Int. Conf. on Advanced Concepts for Intelligent Vision Systems Theory and Applications, 2001.
  • Neural Prediction of Hydrogen in Vacuum Tank Degassing (E. Saarelainen, J.-K. Kamarainen, H. Kälviäinen and R. Väinölä), In Iron & Steelmaker, volume 28, 2001.

2000

  • Neural Prediction of Hydrogen in Vacuum Tank Degassing (J.-K. Kamarainen, H. Kälviäinen, E. Saarelainen and R. Väinölä), In 58th Electric Furnace Conference and 17th Process Technology Conf., 2000.
  • Visual Quality Control of the Vacuum Tank Degassing (J.-K. Kamarainen, H. Kälviäinen, K. Terho and E. Saarelainen), In IFAC Workshop on Future Trends in Automation in Mineral and Metal Processing, 2000.
  • Invariant Shape Recognition using Global Gabor Features (V. Kyrki, J.-K. Kamarainen and H. Kälviäinen), Technical report 72, Lappeenranta University of Technology, Department of Information Technology, 2000.

1999

  • Teräksen vakuumikäsittelyn visuaalinen laadunarviointi (J.-K. Kamarainen), Master’s thesis, Lappeenranta University of Technology, 1999.