Abstract
Analyzing human faces is a traditional topic in computer vision research. For this task, model based approaches have been proven adequate to extract high-level information in many applications. However, they require a robust estimation of model parameters to work reliably. To tackle this challenge, we train displacement experts that serve as an update function on initial model parameter configurations. Unfortunately, building displacement experts that work robustly even in unconstrained environments is a non-trivial task. Therefore, we rely on a priori information about the structure of human faces by integrating an image representation that reflects the location of several facial components, so called “multi-band images”. By combining multi-band images and learned displacement experts, we propose a novel face model fitting approach. An evaluation on the “Labeled Faces In The Wild” database demonstrates, that this approach provides robust fitting results even in unconstrained environments.
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Christoph Mayer studied Computer Science at the Technische Universität München from 2000 to 2007 and received his doctoral degree in 2012. While he was working on his Ph.D, he has been working in the German Cluster of Excellence “Cognition for Technical Systems” in the Intelligent Autonomous Systems Group. His research interests were in the field of face model fitting, facial expression recognition and emotion recognition. He has been first author of the paper “Adjusted Pixel Features for Facial Component Classification” that appeared in the Vision and Image Computing Journal in 2009 and has been awarded with the best paper award in 2009 for the paper “Facial Expression Recognition with 3D Deformable Models” that has been presented at the conference “Advances in Computer-Human Interaction”. His current research interest is in the automatic analysis of soccer games from optical camera data.
Bernd Radig is principal investigator and member of the executive board of the German national cluster of excellence CoTeSys (Cognition for Technical Systems) (since 2006). He received his diploma degree in Physics in 1972 from the University of Bonn and the doctor degree in Computer Science in 1978 from the University of Hamburg. There he got his venia legendi and finished his habilitation dissertation in 1982. He was Assistant and Associate Professor in Hamburg (1982–1986) and full professor, chair of Image Understanding and Knowledge Based Systems, Fakultt fr Informatik, Technische Universität München (1986–2009). He is a member of the Emeriti of Excellence programme. He was chairman and founder of the Association of Bavarian Research Cooperations (1993–2007), a unique network of scientists, specialising in challenging disciplines in accordance with Bavarian enterprises. 1988 he founded the Bavarian Research Centre for Knowledge Based Systems (FOR-WISS), an institute common to the three universities TU Mnchen, Erlangen and Passau. He was general chairman of the annual symposium of the German Association for Pattern Recognition in 1981, 1991, 2001 as well as of the European Conference on Artificial Intelligence (ECAI), 1988. He is active as organizer and programme committee member of the German-Russian Workshop on Pattern Recognition. He holds the German Order of Merit (1992) and the award Pro Meritis Scientiae et Litterarum of the State of Bavaria for outstanding contributions to science and art (2002). His current research activities are in real-time image sequence understanding for applications in robotics, sports or driver assistance systems.
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Mayer, C., Radig, B. Face model fitting with learned displacement experts and multi-band images. Pattern Recognit. Image Anal. 23, 287–295 (2013). https://doi.org/10.1134/S1054661813020119
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DOI: https://doi.org/10.1134/S1054661813020119