Statistical Motion Segmentation and Object Tracking without a-priori models
نویسنده
چکیده
A novel statistical approach for detection and tracking of objects is presented here uses both edge and color information in a particle filter. The approach does not need any prior models of the objects of interest or of the scene. It starts with homogenous regions as tracking primitives and creates complex objects by merging similar moving regions. Even partially occluded objects in a sequence captured by a moving camera can be tracked efficiently and robust.
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