28 November 2007 A scale rotation adaptive new mean shift tracking method
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The mean shift algorithm is an efficient technique for tracking 2D blobs through an image. The scale of the mean shift kernel is a crucial parameter. Classic Mean shift based tracking algorithm uses fixed kernel-bandwidth, which limits the performance when the object scale exceeds the size of the tracking window. Although some modified algorithms can settle the problem of object zooming in a way, these algorithms are helpless to the object rotation. Based on the analysis of the scale-space theory and the current Mean shift algorithms, a scale and rotation adaptive mean shift tracking algorithm is proposed. Experimental results show that the new method can effectively and accurately obtain the best description of the target areas for the first frame, and the new mean shift tracking algorithm can adapt to any kind of object's movements.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Heng Zhang, Heng Zhang, Lichun Li, Lichun Li, You Li, You Li, Qifeng Yu, Qifeng Yu, } "A scale rotation adaptive new mean shift tracking method", Proc. SPIE 6833, Electronic Imaging and Multimedia Technology V, 68330S (28 November 2007); doi: 10.1117/12.757134; https://doi.org/10.1117/12.757134

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