Egor Bondarev is an Assistant Professor in the Video Coding and Architectures group of TU/e, focusing on research areas such as multi-modal sensor fusion, smart surveillance with multi-camera systems and photorealistic 3D reconstruction of environments. Bondarev leads an internal research cluster on real-time data fusion from multi-modal sensors, integrating thermal, depth, laser and RGB information. This research cluster currently consists of five PhD students and a number of MSc students. Egor Bondarev is also involved in several European research projects and is currently a TU/e project leader in the large international projects PaSSANT, PS-CRIMSON and APPS. These projects all address the challenges of multi-modal multi-camera smart surveillance. Bondarev is strongly focused on valorization and exploitation of the algorithms developed in the VCA group. He initiated and organized deployment of the developed vision technologies to ST Microelectronics (France), ViNotion (Netherlands), INRIA (France) and ProDrive (Netherlands). As a lecturer, Bondarev responsible for the master’s degree course on Computer Vision and 3D Data Processing and also teaches the bachelor’s degree course Computation I. He has written and co-authored over 50 publications on real-time computer vision and image/3D processing algorithms.
Egor Bondarev received his MSc degree in robotics and informatics from the State Polytechnic University (Belarus Republic) in 1997. In the four years after, he worked as an engineer at the Invention Machine Corp. In 2009, Bondarev obtained his PhD degree in Computer Science from Eindhoven University of Technology (TU/e). He then took on the position of Assistant Professor in the Video Coding Architectures (VCA) group at TU/e.
Towards parameter-optimized vessel re-identification based on IORnet19th International Conference on Computational Science, ICCS 2019 (2019)
Self-learning framework with temporal filtering for robust maritime vessel detection7th International Workshop on Representations, Analysis and Recognition of Shape and Motion from Imaging Data, RFMI 2017 (2019)
Cascaded CNN method for far object detection in outdoor surveillance14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018 (2019)
Aggregated deep local features for remote sensing image retrievalRemote Sensing (2019)
Improving person re-identification performance by customized dataset and person detectionIS&T International Symposium on Electronic Imaging 2019, Image Processing: Algorithms and Systems XVII (2019)