Visual Saliency Based Object Tracking

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Visual Saliency Based Object Tracking
Abstract. This paper presents a novel method of on-line object tracking with the static and motion saliency features extracted from the video frames locally, regionally and globally. When detecting the salient object, the saliency features are effectively combined in Conditional Random Field (CRF). Then Particle Filter is used when tracking the detected object. Like the attention shifting mechanism of human vision, when the object being tracked disappears, our tracking algorithm can change its target to other object automatically even without re-detection. And different from many other existing tracking methods, our algorithm has little dependence on the surface appearance of the object, so it can detect any category of objects as long as they are salient, and the tracking is robust to the change of global illumination and object shape. Experiments on video clips of various objects show the reliable results of our algorithm.
Geng Zhang, Zejian Yuan, Nanning Zheng, Xingdong S
Added 25 May 2010
Updated 25 May 2010
Type Conference
Year 2009
Where ACCV
Authors Geng Zhang, Zejian Yuan, Nanning Zheng, Xingdong Sheng, Tie Liu
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