In the past 20 years, computer vision has been transformed from a purely theoretical subject producing algorithms failing on all but a few carefully chosen images into a large discipline...
In the past 20 years, computer vision has been transformed from a purely theoretical subject producing algorithms failing on all but a few carefully chosen images into a large discipline where the path from a paper to a successful start-up company is surprisingly short. Multinationals like Google, Microsoft, Facebook, Adobe or Amazon employ dozens if not hundreds of computer vision experts.
Detection and localisation of objects is one of the areas where significant progress has been achieved recently. It is now possible to answer, in near-real time, not only questions like "How many faces are there in the image?" but, for a broad class of objects, even "What is depicted in the picture?". Current research indicates there is no all-encompassing object detection algorithm, and a taxonomy of problems and approaches that has emerged will be introduced. I will present algorithms that have significantly pushed the state of the art and demonstrate the growing use of machine learning techniques on computer vision, focusing on the Viola-Jones detection method with sequential decision making. The talk will be concluded with remarks on results of the Bag of Words and Deep Neural Net methods.
Jiří Matas is a full professor at the Centre for Machine Perception, Czech Technical University in Prague (CTU). He holds a PhD degree from the University of Surrey, UK (1995). He has published more than 200 papers in refereed journals and conferences. His publications have approximately 6000 citations in the ISI Thomson-Reuters Science Citation Index and about 18000 in Google scholar. His h-index is 25 (ISI) and 48 (Google scholar) respectively. He received the best paper prize at the British Machine Vision Conferences in 2002 and 2005, at the Asian Conference on Computer Vision in 2007, and at the Scandinavian Conference on Image Analysis and at the Image and Vision Computing New Zealand Conference in 2013. His students received a number of awards, e.g., Best Student paper at ICDAR 2013, Google Fellowship 2013, and various "Best Thesis" prizes. J. Matas has served in various roles at major international conferences (e.g. ICCV, CVPR, ICPR, NIPS, ECCV), co-chairing ECCV 2004 and CVPR 2007. He is on the editorial board of IJCV and was the Associate Editor-in-Chief of IEEE T. PAMI. He is a member of the ERC Computer Science and Informatics panel. For details, see http://cmp.felk.cvut.cz/~matas.
His research interests include object recognition, image retrieval, tracking, sequential pattern recognition, invariant feature detection, and Hough Transform and RANSAC-type optimization. He is a co-founder of Eyedea recognition, http://www.eyedea.cz/, the first CTU spin-off. He is a co-inventor of several patents.
Its program consists of a one-hour lecture followed by a discussion. The lecture is based on an (internationally) exceptional or remarkable achievement of the lecturer, presented in a way which is comprehensible and interesting to a broad computer science community. The lectures is in English.
The seminar is organized by the organizational committee consisting of Roman Barták (Charles University, Faculty of Mathematics and Physics), Michal Chytil (Czech Academy of Sciences, Computer Science Institute), Pavel Kordík (Czech Tech. Univ., Faculty of Information Technologies), Jan Kybic (Czech Tech. Univ., Faculty of Electrical Engineering), Michal Pěchouček (Czech Tech. Univ., Faculty of Electrical Engineering), Jiří Sgall (Charles University, Faculty of Mathematics and Physics), Vojtěch Svátek (University of Economics, Faculty of Informatics and Statistics), Michal Šorel (Czech Academy of Sciences, Institute of Information Theory and Automation), Tomáš Werner (Czech Tech. Univ., Faculty of Electrical Engineering), and Filip Železný (Czech Tech. Univ., Faculty of Electrical Engineering)
The idea to organize this seminar emerged in discussions of the representatives of several research institutes on how to avoid the undesired fragmentation of the Czech computer science community.