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Computer Vision Group

TAU Computing Sciences

Publications

396 results

2023

  • 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. [youtube]
  • Prioritized offline Goal-swapping Experience Replay (W. Yang, J. Pajarinen and J.-K. Kämäräinen), In Int. Conf. On Learning Representations Workshops (ICLRW), 2023. [pdf]
  • 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. [pdf]
  • A Depth Backbone for Image Classification (Ville Vianto), Technical report, Tampere University, 2023. [pdf]
  • 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.
  • 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]
  • Frequency Domain Image Classification with Convolutional Neura Networks (Sophie Tötterström), Technical report, Tampere University, 2023. [pdf] [code]
  • Spoken Wake-word Detection for Conversational Avatar (Simon Savukoski), Technical report, Tampere University, 2023. [pdf] [code]
  • Deep Learning with Fourier Transformed Images (Noora Sassali), Technical report, Tampere University, 2023. [pdf] [code]
  • LiDAR Place Recognition with Image Retrieval (Jukka Peltomäki), PhD thesis, Tampere University, 2023. [pdf]
  • 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.
  • 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. [pdf]
  • 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]
  • Raspberry Pi Art Display with Neural Style Transfer (Aleksi Nissilä), Technical report, Tampere University, 2023. [pdf] [code]
  • 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]
  • Image Morphing Sequences (Henrik Lauronen), Technical report, Tampere University, 2023. [pdf]
  • FinnWoodlands Dataset (Lagos J., Lempiö U. and Rahtu E.), In Scandinavian Conference on Image Analysis (SCIA), 2023. [pdf]
  • Single Pixel Spectral Color Constancy (S. Koskinen, E. Acar and J.-K. Kämäräinen), In International Journal of Computer Vision, 2023. [doi]
  • Drift Correction for SLAM Point Clouds: Smooth Natural Neighbor Interpolation (Kaapo Kontinen), Technical report, Tampere University, 2023. [pdf] [code]
  • NVIDIA Isaac and Robot Operating System 2 : Integrating ROS2 with Isaac Sim for robot navigation (Dan Katainen), Technical report, Tampere University, 2023. [pdf]
  • Koneoppimisen perusteet (Joni Kämäräinen), Gaudeamus, 2023. [pdf]
  • Animation of a speaking chatbot (Konsta Jurvanen), Technical report, Tampere University, 2023. [pdf] [code]
  • SLAM Drift and Localization Error Reduction with RTAB-Map tools (Siina Ingren), Technical report, Tampere University, 2023. [pdf]
  • On Deep Image Deblurring: The Blur Factorization Approach (Samuli Hynninen), Master’s thesis, Tampere University, 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.
  • 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.
  • 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. [pdf]
  • 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]
  • Long-term Visual Place Recognition Under Varying Conditions (Farid Alijani), PhD thesis, Tampere University, 2023. [pdf]

2022

  • V-SlowFast Network for Efficient Visual Sound Separation (Zhu L. and Rahtu E.), In IEEE Winter Conference on Applications of Computer Vision (WACV), 2022. [pdf]
  • 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]
  • 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. [pdf]
  • Active Short-Long Exposure Deblurring (D. Yang, S. Koskinen and J.-K. Kämäräinen), In Int. Conf. on Pattern Recognition (ICPR), 2022. [pdf]
  • Vision and Depth Based Computerized Anthropometry and Object Tracking (Song Yan), PhD thesis, Tampere University, 2022. [pdf]
  • 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. [pdf]
  • 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. [pdf]
  • 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]
  • 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. [pdf]
  • 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.
  • Online panoptic 3D reconstruction as a Linear Assignment Problem (Raivio L. and Rahtu E.), In International Conference on Image Analysis and Processing (ICIAP), 2022. [pdf]
  • 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. [pdf]
  • Visual Localization Using Mobile Phone (Joona Nousiainen), Technical report, Tampere University, 2022. [pdf] [code]
  • 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. [pdf]
  • Adaptive Monte Carlo Localization in ROS (Tuomas Lauttia), Technical report, Tampere University, 2022. [pdf]
  • 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 Čehovin 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. [pdf]
  • Vision Based Autonomous Driving : Hardware and Software Implementation (Olli Koskelainen), Technical report, Tampere University, 2022. [pdf]
  • Estimating three-dimensional motion using IMU sensors (Marko Kivikangas), Technical report, Tampere University, 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]
  • 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]
  • 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.
  • Camera Pose Estimation from Street-view Snapshots and Point Clouds (Junsheng Fu), PhD thesis, Tampere University, 2022. [pdf]
  • 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. [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. [pdf]
  • 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]
  • 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.

2021

  • 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. [pdf]
  • 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]
  • Leveraging Category Information for Single-Frame Visual Sound Source Separation (Zhu L. and Rahtu E.), In European Workshop on Visual Information Processing (EUVIP), 2021. [pdf]
  • 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. [pdf] [youtube]
  • 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]
  • Depth-only Object Tracking (S. Yan, J. Yang, A. Leonardis and J.-K. Kämäräinen), In British Machine Vision Conference (BMVC), 2021. [pdf] [code]
  • Vision-based Body Measurements (Jori Väinölä), Technical report, Tampere University, 2021. [pdf] [code]
  • FACEGAN: Facial Attribute Controllable rEenactment GAN. (Tripathy S., Kannala J. and Rahtu E.), 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. [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]
  • 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]
  • 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.
  • 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. [pdf]
  • 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]
  • 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. [pdf]
  • 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. [pdf]
  • 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. [pdf]
  • 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. [pdf]
  • Single Pixel Spectral Color Constancy (S. Koskinen, E. Acar and J.-K. Kämäräinen), In British Machine Vision Conference (BMVC), 2021. [pdf]
  • Taming Visually Guided Sound Generation (Iashin V. and Rahtu E.), In British Machine Vision Conference (BMVC), 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. [pdf]
  • 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]
  • 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]
  • Computer Vision for Robotics: Feature Matching, Pose Estimation and Safe Human-Robot Collaboration (Antti Hietanen), PhD thesis, Tampere University, 2021. [pdf]
  • Deep Open Domain Chatbots (Tariq Harb), Technical report, Tampere University, 2021. [pdf] [code]
  • FATALRead – Fooling visual speech recognition models (Gupta A., Gupta P. and Rahtu E.), In Applied Intelligence, 2021. [pdf]
  • Selective Probabilistic Classifier Based on Hypothesis Testing (Germi S., Rahtu E. and Huttunen H.), In European Workshop on Visual Information Processing (EUVIP), 2021. [pdf]
  • Comparison of monolithic and hybrid controllers for multi-objective sim-to-real learning (Atakan Dag), Master’s thesis, Tampere University, 2021. [pdf] [code]
  • 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]
  • 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.
  • Sample selection for efficient image annotation (Adhikari B., Rahtu E. and Huttunen H.), In European Workshop on Visual Information Processing (EUVIP), 2021. [pdf]
  • 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.
  • 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. [pdf]

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.
  • 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.
  • 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.
  • 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]
  • Anthropometric clothing measurements from 3D body scans (S. Yan, J. Wirta and J.-K. Kämäräinen), In Machine Vision and Applications, volume 31, 2020. [pdf] [doi] [data]
  • Silhouette Body Measurement Benchmarks (S. Yan, J. Wirta and J.-K. Kämäräinen), In Int. Conf. on Pattern Recognition (ICPR), 2020. [pdf] [doi] [data]
  • Implementing VR feature camera on Android platform (Aleksi Viljanen), Technical report, Tampere University, 2020. [pdf] [code]
  • 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.
  • 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.
  • Learning to Align Images (Eero Ruuhikorpi), Technical report, Tampere University, 2020. [pdf] [code]
  • Computational Color Constancy: From Pixel to Video with a Stop at Convolutional Neural Network (Yanlin Qian), PhD thesis, Tampere University, 2020. [pdf]
  • 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]
  • 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. [pdf]
  • 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]
  • 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.
  • Sequential View Synthesis with Transformer (Nguyen P., Huynh L., Rahtu E. and Heikkilä J.), In Asian Conference on Computer Vision (ACCV), 2020.
  • Autonomous Racing Robot: Hardware and Software Implementation (Eetu Manninen), Technical report, Tampere University, 2020. [pdf] [code]
  • The Eighth Visual Object Tracking VOT2020 Challenge Results (Matej Kristan, Ales Leonardis, Jiri Matas, Michael Felsberg, Roman Pflugfelder, Joni-Kristian Kamarainen, Luka Čehovin 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. [pdf]
  • 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]
  • Simultaneous Localization and Mapping with Apple ARKit (Christian Kaarre), Technical report, Tampere University, 2020. [pdf] [code] [youtube]
  • Smoke and Fire Segmentation from Images Using Weakly Supervised Neural Networks (Raafael Juntti), Technical report, Tampere University, 2020. [pdf]
  • 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. [pdf]
  • Multi-Modal Dense Video Captioning (Iashin V. and Rahtu E.), In The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2020. [pdf]
  • 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.
  • 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]
  • 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.

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]
  • 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.
  • 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]
  • UR5-robottikäden reaaliaikainen ohjaus (Valtteri Viikari), Technical report, Tampere University, 2019. [pdf]
  • 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.
  • 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.
  • 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.
  • Trend Analysis in AI Research Over Time Using NLP Techniques (Eemeli Saari), Technical report, Tampere University, 2019. [pdf]
  • 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) [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.
  • Flash Lightens Gray Pixels (Y. Qian, S. Yan, J.-K. Kämäräinen and J. Matas), In Int. Conf. on Image Processing (ICIP), 2019. [pdf]
  • 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]
  • Anki Cozmo -ohjelmointi (Kirsi Pietilä), Technical report, Tampere University, 2019. [pdf]
  • 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]
  • 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]
  • 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]
  • 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.
  • 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.
  • 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.
  • 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]
  • 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]
  • 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]
  • 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]
  • 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]
  • 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]
  • 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]
  • MLAttack: Fooling Semantic Segmentation Networks by Multi-layer Attacks. (Gupta P. and Rahtu E.), In German Conference on Pattern Recognition (GCPR), 2019.
  • 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.
  • 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]
  • 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]
  • Kuvan korjaaminen ilman sen näkemistä (Jani Brjörklund), Technical report, Tampere University, 2019. [pdf]
  • Visual Reward for Autonomous Driving (Lauri Alho), Technical report, Tampere University, 2019. [pdf]
  • 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]

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]
  • 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.
  • 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.
  • 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]
  • 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.
  • 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.
  • Inertial Odometry on Handheld Smartphones. (Solin A., Cortes S., Rahtu E. and Kannala J.), In International Conference on Information Fusion (FUSION), 2018.
  • 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]
  • 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]
  • 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]
  • Efficient and Robust Methods for Audio and Video Signal Analysis (K. Mahkonen), PhD thesis, Tampere University of Technology, 2018. [pdf]
  • 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]
  • 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.
  • 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]
  • 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]
  • 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-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]
  • 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]
  • 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]
  • 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.
  • Convolutional Low-Resolution Fine-Grained Classification (D. Cai, K. Chen, Y. Qian and J.-K. Kämäräinen), In Pattern Recognition Letters, 2018. [pdf] [doi]
  • 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]

2017

  • 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]
  • Dominant Convolutional Feature Channels for Image Subcategory Clustering (Peng Yao), Master’s thesis, Tampere University of Technology, 2017. [pdf]
  • 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]
  • Hierarchical regression learning for car pose estimation (Dan Yang), Master’s thesis, University of Tampere, 2017. [pdf]
  • 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]
  • 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.
  • Video event classification using 3D convolutional neural networks (Iikka Teivas), Master’s thesis, Tampere University of Technology, 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.
  • 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]
  • 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]
  • 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]
  • Region-based Depth Recovery for Highly Sparse Depth Maps (S. Pertuz and J.-K. Kämäräinen), In Int. Conf. on Image Processing (ICIP2017), 2017. [pdf]
  • 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.
  • 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.
  • Image-based Localization using Hourglass Networks. (Melekhov I., Ylioinas J., Kannala J. and Rahtu E.), In Geometry Meets Deep Learning ICCV Workshop (ICCVW), 2017.
  • Universal Robotics -käsivarren ohjaus Kinectillä (Samuli Koivisto), Technical report, Tampere University of Signal Processing, 2017. [pdf] [code]
  • 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]
  • Spectral Attribute Learning for Visual Regression (K. Chen, K. Jia, Z. Zhang and J.-K. Kämäräinen), In Pattern Recognition, volume 66, 2017. [pdf] [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]
  • 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. [pdf] [doi]

2016

  • 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]
  • 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]
  • 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.
  • Structured Deep Learning for Fine-grained Visual Classification (Yanlin Qian), 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]
  • Dense 3D Models From a Single RGB-D View (Antti Pohjola), Master’s thesis, Tampere University of Technology, 2016. [pdf]
  • 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.
  • 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.
  • 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.
  • Siamese network features for image matching. (Melekhov I., Kannala J. and Rahtu E.), In International Conference on Pattern Recognition (ICPR), 2016.
  • 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]
  • 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]
  • 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.
  • 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.
  • Car Type Recognition with Deep Neural Networks (H. Huttunen, F. Shokrollahi Yancheshmeh and Ke Chen), In IEEE Intelligent Vehicles Symposium, 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]
  • 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]
  • 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]
  • Facial Age Estimation Using Robust Label Distribution (K. Chen, Z. Zhang and J.-K. Kämäräinen), In ACM Multimedia Conference (ACMMM), 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]
  • 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]
  • Video Summarization with Key Frames (Antti Ainasoja), Master’s thesis, Tampere University of Technology, 2016.

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.
  • 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.
  • 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.
  • 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]
  • 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.
  • Kamerapohjainen paikannus (Ansse Saarimäki), Technical report, Tampere University of Signal Processing, 2015. [pdf]
  • Generative Part-Based Gabor Object Detector (E. Riabchenko and J.-K. Kämäräinen), In Pattern Recognition Letters, volume 68, 2015. [pdf] [code]
  • Generative Part-Based Gabor Object Detector (E. Riabchenko), PhD thesis, Lappeenranta University of Technology, 2015. [pdf]
  • 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]
  • Incremental Learning in Deep Neural Networks (Y. Liu), 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.
  • Local Features for Visual Object Class Matching and Video Scene Detection (A. Hietanen), Master’s thesis, Tampere University of Technology, 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]
  • Visualizing Retinal Vessel Dynamics Using Self-Organizing Map (Satu Haikonen), Technical report, Tampere University of Signal Processing, 2015.
  • 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]
  • 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]

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. [pdf]
  • 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.
  • 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.
  • Live RGB-D Camera Tracking for Television Production Studios (T. Tykkälä, A.I. Comport and J.-K. Kämäräinen and H. Hartikainen), In Journal of Visual Communication and Image Representation, volume 25, 2014. [pdf] [code]
  • 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.
  • 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.
  • 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.
  • 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]
  • Unsupervised Alignment of Objects in Images (Fatemeh Shokrollahi Yancheshmeh), Master’s thesis, Tampere University of Technology (TUT), 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]
  • 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]
  • 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.
  • 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]
  • 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.
  • Local Features in Image and Video Processing – Object Class Matching and Video Shot Detection (J. Lankinen), PhD thesis, Lappeenranta University of Technology, 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.
  • 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]
  • 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]
  • Learning to Count with Back-Propagated Information (K. Chen and J.-K. Kämäräinen), In 22th Int. Conf. on Pattern Recognition (ICPR2014), 2014. [pdf]
  • 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.

2013

  • 18th Scandinavian Conf. on Image Analysis, (J.-K. Kämäräinen, M. Koskela, eds.), Springer, 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]
  • 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]
  • Real-Time Image-Based RGB-D Camera Motion Tracking and Environment Mapping (T.M. Tykkälä), PhD thesis, Lappeenranta University of Technology, 2013. [pdf] [code]
  • Saliency detection using joint temporal and spatial decorrelation. (Tavakoli H., Rahtu E. and Heikkilä J.), In Scandinavian Conference on Image Analysis (SCIA), 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.
  • Stochastic bottom-up fixation prediction and saccade generation. (Tavakoli H., Rahtu E. and Heikkilä J.), In Image and Vision Computing (IVC), volume 31, 2013.
  • Supervised Object Class Colour Normalisation (E. Riabchenko, J. Lankinen, A.G. Buch and J.-K. Kämäräinen and N. Krueger), 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]
  • 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]
  • 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. [pdf]
  • 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.
  • 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.
  • 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]
  • 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]
  • Non maximal suppression in cascaded ranking models. (Blaschko M B., Kannala J. and Rahtu.), In Scandinavian Conference on Image Analysis (SCIA), 2013.

2012

  • Federated Computer Science Event, (S. Tarkoma, J.-K. Kamarainen, T. Pahikkala, eds.), Unigrafia, 2012. [pdf]
  • BSIF: binarized statistical image features. (Rahtu E and Kannala J.), In International Conference on Pattern Recognition (ICPR), 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.
  • 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.
  • 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]
  • Visual Saliency and Categorisation of Abstract Images (M. Laine-Hernandez, T. Kinnunen, J.-K. Kamarainen, L. Lensu and H. Kälviäinen and P. Oittinen), In 21th Int. Conf. on Pattern Recognition (ICPR2012), 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]
  • 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]
  • 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]
  • Gabor Features in Image Analysis (J.-K. Kamarainen), In Int. Conf. on Image Processing Theory, Tools and Applications (IPTA2012), 2012. [pdf]
  • 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]
  • 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.

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.
  • Learning a Category Independent Object Detection Cascade. (Rahtu E., Kannala J. and Blaschko M B.), In IEEE International Conference on Computer Vision (ICCV), 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.
  • 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.
  • Projector calibration by “inverse camera calibration” (I. Martynov, J.-K. Kamarainen and L. Lensu), In Scandinavian Conf. on Image Analysis (SCIA2011), 2011. [pdf]
  • Local Feature Based Unsupervised Alignment of Object Class Images (J. Lankinen and J.-K. Kamarainen), In British Machine Vision Conference (BMVC2011), 2011. [pdf]
  • Facial Feature Representation (J.-K. Kamarainen, A. Hadid and M. Pietikäinen), Chapter in Handbook of Face Recognition, Springer, 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.
  • 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]
  • Thresholding based detection of fine and sparse details (A. Drobchenko, J.-K. Kamarainen, L. Lensu, J. Vartiainen and H. Kälviäinen and T. Eerola), In Frontiers of Electrical and Electronic Engineering in China, volume 6, 2011.

2010

  • Compressing sparse feature vectors using random ortho-projections. (Rahtu E., Salo M. and Heikkilä J.), In International Conference on Pattern Recognition (ICPR), 2010.
  • Segmenting salient objects from images and videos. (Rahtu E., Kannala J., Salo M. and Heikkilä J.), In European Conference on Computer Vision (ECCV), 2010.
  • Narrow Baseline GLSL Multiview Stereo (P. Paalanen and J.-K. Kamarainen), In 3D Data Processing, Visualization and Transmission (3DPVT), 2010. [pdf] [code]
  • 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]
  • 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]
  • 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]
  • Improved blur insensitivity for decorrelated local phase quantization. (Heikkilä J., Rahtu E. and Ojansivu V.), In International Conference on Pattern Recognition (ICPR), 2010.
  • The structural form in image categorization. (Hanni J., Rahtu E. and Ojansivu V.), In International Conference on Computer Vision Theory and Applications (VISAPP), 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]

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.
  • Affine invariant features in pattern recognition. (Rahtu E and Heikkilä J.), Chapter in Handbook of Pattern Recognition and Computer Vision, World Scientific, 2009.
  • A simple and efficient saliency detector for background subtraction. (Rahtu E and Heikkilä J.), In Workshop on Visual Surveillance (ICCV-VS), 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]
  • 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.
  • 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.
  • 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]
  • 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.
  • 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]
  • 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.

2008

  • Detection of irregularities in regular patterns (J. Vartiainen, A. Sadovnikov, J.-K. Kamarainen and L. Lensu and H. Kälviäinen), In Machine Vision and Applications, volume 19, 2008. [pdf]
  • Towards online 3D reconstruction (P. Paalanen, V. Kyrki and J.-K. Kamarainen), In European Conference on Computer Vision (ECCV) Workshops, 2008. [pdf]
  • 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.
  • 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.
  • 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]
  • 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.
  • 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.
  • 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.

2007

  • A multiscale framework for affine invariant pattern recognition and registration. (Rahtu E.), 2007.
  • Affine registration using multiscale approach. (Rahtu E., Salo M. and Heikkilä J.), In Finnish Signal Processing Symposium (FINSIG), 2007.
  • Nonlinear functionals in the construction of affine invariants. (Rahtu E., Salo M. and Heikkilä J.), In Scandinavian Conference on Image Analysis (SCIA), 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.
  • 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.
  • 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.
  • Asiantuntijatiedon käyttö silmänpohjakuvien automaattisessa tulkinnassa (T. Kauppi, V. Kalesnykiene, L. Lensu, J.-K. Kamarainen, I. Sorri, A. Raninen, R. Voutilainen, H. Kälviäinen and J. Pietilä and H. Uusitalo), In , 2007.
  • 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.
  • 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.
  • 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.
  • 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]
  • 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.
  • 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.
  • Object class detection using local image features and point pattern matching constellation search (A. Drobchenko, J. Ilonen, J.-K. Kamarainen, A. Sadovnikov and H. Kälviäinen and M. Hamouz), In Scandinavian Conf. on Image Analysis (SCIA2007), 2007.

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.
  • Automating visual inspection of print quality (J. Vartiainen, S. Lyden, A. Sadovnikov, J.-K. Kamarainen and L. Lensu and H. Kälviäinen), In Int. Conf. on Image Analysis and Recognition, volume 2, 2006.
  • Detecting irregularities in regular patterns (J. Vartiainen, L. Lensu, J.-K. Kamarainen and A. Sadovnikov and H. Kälviäinen), In 18th Int. Conf. on Pattern Recognition (ICPR2006), 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.
  • Measuring Translation Shiftability of Frames (J. Sampo, J.-K. Kamarainen, M. Heiliö and H. Kälviäinen), In Computers & Mathematics with Applications, volume 52, 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.
  • 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.
  • A new affine invariant image transform based on ridgelets. (Rahtu E., Salo M. and Heikkilä J.), In British Machine Vision Conference (BMVC), 2006.
  • Multiscale autoconvolution histograms for affine invariant pattern recognition. (Rahtu E., Salo M. and Heikkilä J.), In British Machine Vision Conference (BMVC), 2006.
  • Generalized affine moment invariants for object recognition. (Rahtu E., Salo M., Heikkilä J. and Flusser J.), In International Conference on Pattern Recognition (ICPR), 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]
  • 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.
  • 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]
  • 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]
  • Toward Automatic Forecasts for Diffusion of Innovations (J. Ilonen, J.-K. Kamarainen, K. Puumalainen and S. Sundqvist and H. Kälviäinen), In Technological Forecasting & Social Change, volume 73, 2006. [pdf]
  • Object categorization using self-organization over visual appearance (J. Ilonen and J.-K. Kamarainen), In Int. Joint Conf. on Neural Networks (IJCNN2006), 2006.

2005

  • Detection of Irregularities in Regular Dot Patterns (A. Sadovnikov, J. Vartiainen, J.-K. Kamarainen and L. Lensu and H. Kälviäinen), In IAPR Conf. on Machine Vision Applications, 2005.
  • Detection of irregularities in regular dot patterns (A. Sadovnikov, J. Vartiainen, J.-K. Kamarainen and L. Lensu and H. Kälviäinen), Technical report 93, Lappeenranta University of Technology, Department of Information Technology, 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.
  • 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.
  • 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.
  • 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.
  • 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 registration with multi-scale autoconvolution. (Kannala J., Rahtu E. and Heikkilä J.), In International Conference on Image Processing (ICIP), 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.
  • Fundamental Frequency and Global Gabor Features (J.-K. Kamarainen, V. Kyrki and H. Kälviäinen), 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.
  • Intelligent Information Processing: Machine Vision and Pattern Recognition Applications (H. Kälviäinen and J.-K. Kamarainen), In Pattern Recognition and Image Analysis, volume 15, 2005.
  • 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.
  • Diagnosis Tool for Motor Condition Monitoring (J. Ilonen, J.-K. Kamarainen, T. Lindh, J. Ahola and H. Kälviäinen and J. Partanen), In IEEE Transactions on Industry Applications, volume 41, 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.
  • 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]
  • Automated Pattern Recognition for the Detection of Diabetic Changes in Digital Fundus Images (J. Forsstrom, V. Kalesnykiene, M. Kuivalainen, I. Sorri and H. Uusitalo and J.-K. Kamarainen), In ARVO 2005 Annual Meeting, 2005.
  • Thresholding Based Detection of Fine and Sparse Details (A. Drobchenko, J. Vartiainen, J.-K. Kamarainen and L. Lensu and H. Kälviäinen), In IAPR Conf. on Machine Vision Applications, 2005. [pdf]
  • Thresholding Based Detection of Fine and Sparse Details (A. Drobchenko, J. Vartiainen, J.-K. Kamarainen and L. Lensu and H. Kälviäinen), Technical report 99, Department of Information Technology, Lappeenranta University of Technology, 2005.

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.
  • Object recognition using multi-scale autoconvolution. (Rahtu E.), 2004.
  • Convexity recognition using multi-scale autoconvolution. (Rahtu E., Salo M. and Heikkilä J.), In International Conference on Pattern Recognition (ICPR), 2004.
  • Object classification with multi-scale autoconvolution. (Rahtu E and Heikkilä J.), In International Conference on Pattern Recognition (ICPR), 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]
  • 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.
  • PAPVISION: Paper and Board Printability Tests by Machine Vision in the Paper Making and Printing Industry (H. Kälviäinen, A. Sadovnikov, P. Salmela, A. Drobchenko and J.-K. Kamarainen, L. Lensu, P. Saarinen, P. and J. Vartiainen), In ECCV Workshop on Applications of Computer Vision, 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.
  • 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.

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.
  • 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.
  • 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.
  • Statistical Signal Discrimination for Condition Diagnosis (J.-K. Kamarainen, V. Kyrki, T. Lindh, J. Ahola and J. Partanen), In Finnish Signal Processing Symposium, 2003.
  • Improving Similarity Measures of Histograms Using Smoothing Projections (J.-K. Kamarainen, V. Kyrki and J. Ilonen), In Pattern Recognition Letters, volume 24, 2003. [pdf]
  • Feature Extraction Using Gabor Filters (J.-K. Kamarainen), PhD thesis, Lappeenranta University of Technology, 2003. [pdf]
  • The Global Diffusion of Internet and Wireless Subscriptions: A Neural Network Approach (J. Ilonen, K. Puumalainen, S. Sundqvist and J.-K. Kamarainen and H. Kälviäinen), In , 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]
  • 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.

2002

  • Forecasting the Critical Mass of Wireless Communications (S. Sundqvist, L. Frank, K. Puumalainen and J.-K. Kamarainen and S. Pitkänen), In Australian and New Zealand Marketing Academy Conf., 2002.
  • 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.
  • 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]
  • Robustness of Gabor Feature Parameter Selection (J.-K. Kamarainen, V. Kyrki and H. Kälviäinen), In IAPR Workshop on Machine Vision Applications, 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.
  • 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.
  • 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), Technical report 78, Lappeenranta University of Technology, Department of Information Technology, 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.

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.
  • 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.
  • Invariant Shape Recognition using Global Gabor Features (V. Kyrki, J.-K. Kamarainen and H. Kälviäinen), In 12th Scandinavian Conf. on Image Analysis (SCIA2001), 2001.
  • Similarity Measures for Ordered Histograms (J.-K. Kamarainen, V. Kyrki and H. Kälviäinen), In 12th Scandinavian Conf. on Image Analysis (SCIA2001), 2001.

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.
  • 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.
  • 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.

1999

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