Segmentation and Tracking Using Color Mixture Models
نویسندگان
چکیده
A system is described that provides robust and real-time focus-of-attention for tracking and segmentation of multicoloured objects. Gaussian mixture models were used to estimate the probability densities of object foreground and scene background colours. Tracking was performed by tting dynamic bounding boxes to image regions of maximum probability. Two scenarios are presented: (1) real-time face tracking based upon a skin colour model and (2) dynamic body segmen-tation for virtual studios based upon combined foreground and background models.
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تاریخ انتشار 1998