Online structured hough forests for visual tracking
Tao Qin, Bineng Zhong, Hanzi Wang · 2013
Segmentation-based tracking methods are popular in alleviating the model drift problem during online-learning of visual trackers. However, one of the limitations of those methods is that tracking results guide the process of segmentation. The model drift problem in tracking may have significant influence on segmentation. In this paper, we propose an online structured Hough Forests to address this limitation. The results of object tracking do not have significant influence on the process of segmentation. Our algorithm shows more robust results on several challenging sequences.