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Institute of Computer Science (ICS)
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|Title||Color-based Tracking of Human Body Parts||>> See brochure|
|Laboratory||Computational Vision and Robotics|
|Contact person||Antonis Argyros
Associate Professor of Computer Science
The Computational Vision and Robotics Laboratory of FORTH-ICS have developed a method for tracking multiple skin colored objects in images acquired by a possibly moving camera. The proposed method encompasses a collection of techniques that enable the modeling and detection of skin-colored objects as well as their temporal association in image sequences. Skin-colored objects are detected with a Bayesian classifier which is bootstrapped with a small set of training data. Tracking over time is realized through a novel technique which can handle multiple skin-colored objects. Such objects may move in complex trajectories and occlude each other in the field of view of a possibly moving camera. Moreover, the number of tracked objects may vary in time. A prototype implementation of the developed system operates on 320x240 live video in real time (30Hz) on a conventional Pentium 4 processor.
The proposed 2D tracker has formed a basic building block for tracking multiple skin colored regions in 3D. More specifically, we have developed a method which is able to report the 3D position of all skin-colored regions in the field of view of a potentially moving stereoscopic camera system. The prototype implementation of the 3D version of the tracker also operates at 30 fps.
On top of this functionality, the tracker is able to deliver 3D contours of all skin colored regions; this is performed at a rate of 22 fps.One of the very important aspects of the developed tracker is that it can be trained to any desired color distribution, which can be subsequently tracked efficiently and robustly with high tolerance in illumination changes.
Due to its robustness and efficiency, the proposed tracker(s) have already been used as important building blocks in a number of diverse applications.
More specifically, the 2D tracker has been employed for:
More details and video demonstrations can be found at: