Real-Time Tracking of Multiple Skin-Colored Objects with a Possibly Moving Camera

This paper presents 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. Then, an off-line iterative training procedure is employed to re- fine the classifier using additional training images. On-line adaptation of skin-color probabilities is used to enable the classifier to cope with illumi- nation changes. 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 oper- ates on 320x240 live video in real time (28Hz) on a conventional Pentium 4 processor. Representative experimental results from the application of this prototype to image sequences are also provided.

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