Self-Adaptive Visual Tracker Based on Background Information
Occlusion is a thorny issue in visual tracking,which may lead to serious drift to the tracking result.In this paper,a new tracker is proposed to deal with occlusion in tracking.Background surroundings to the object are divided into patches as supplementary information for occlusion detection.When the object is partially occluded,compensation will be made to the estimated position thus ensuring a better tracking result.The detector will be activated to search the whole frame for the object when object is missing.Correlation filter is applied to build the classifier for a higher speed and random ferns are used in the detector.Experiments are carried out on OTB benchmark videos and the result indicates the proposed tracker is preferable comparing to state-of-art trackers in handling occlusion.
Visual tracking correlation filters background information object detection
Shuqiao Sun Wenjing Kang
School of Information and Electrical Engineering, Harbin Institute of Technology(Weihai)Weihai, China
国际会议
哈尔滨
英文
1003-1008
2016-07-21（万方平台首次上网日期，不代表论文的发表时间）