Histogram Resolution Determination using the Variance Ratio of the Target and Background for Object Tracking

Takayuki Nishimori, Toyohiro Hayashi, Shuichi Enokida, and Toshiaki Ejima


Computer Vision, Object Tracking, Mean-Shift


An object tracking is one of the most important techniques in digital image processing. The mean-shift tracking algorithm uses the tracker that scans locally according to the gradient of color features so that targets can be estimated faster. However, the mean-shift algorithm only guarantees a locally optimum solution, not a globally optimum solution. Thus, it is difficult to re-track the target automatically once tracking has failed. In this paper, to suppress the local optimal solution, a controlling method of the color histogram representation using the variance ratio of the target and the background color histograms is proposed. Actually, some experimental results showed the effectiveness of the proposal method. And the correlation between the background region area size and the tracking accuracy of proposed method is shown by some experimental results.

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