Object tracking by adaptive modeling
A. Rareş, M.J.T. Reinders · 2002
This paper addresses the problem of object tracking in image sequences. The approach taken is based upon adaptive statistical models. An object selected in a frame by a user is tracked throughout the sequence by using a blob-like description of its features. The object features are continuously updated by using the on-line version of the expectation-maximization algorithm. The proposed object description results in a flexible representation.