A Simple Oriented Mean-Shift Algorithm for Tracking
نویسندگان
چکیده
Mean-Shift tracking gained a lot of popularity in computer vision community. This is due to its simplicity and robustness. However, the original formulation does not estimate the orientation of the tracked object. In this paper, we extend the original mean-shift tracker for orientation estimation. We use the gradient field as an orientation signature and introduce an efficient representation of the gradient-orientation space to speed-up the estimation. No additional parameter is required and the additional processing time is insignificant. The effectiveness of our method is demonstrated on typical sequences.
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The mean shift algorithm is one of the popular methods in visual tracking for non-rigid moving targets. Basically, it is able to locate repeatedly the central mode of a desirable target. Object representation in mean shift algorithm is based on its feature histogram within a non-oriented individual kernel mask. Truly, adjusting of the kernel scale is the most critical challenge in this method. ...
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