中南大学学报（自然科学版）2017，Vol.48Issue(2)：395-403,9.DOI:10.11817/j.issn.1672-7207.2017.02.018
结合运动矢量的分权快速压缩跟踪算法
Fast compressive tracking algorithm based on motion vector and assigning weight value
摘要
Abstract
To reduce the drift phenomenon in object tracking, a candidate object location search method was proposed combining motion vector with super pixel. In order to weaken the influence of complex background and improve the tracking robustness, the features from the blocks in the tracking box were assigned different weights according to their locations. The classifier may get wrong information if it continues learning when the tracking object is largely occluded. A object detection approach was proposed to avoid the false classification in the situations of object occlusion. The experiment results show that the proposed algorithm has better performance and can track successfully and efficiently for a long time, compared with some state-of-the-art works in many complicated situations, e.g. swift movement, object deformation, complex background, occlusion and illumination variation.关键词
目标跟踪/运动矢量/置信值/遮挡检测Key words
object tracking/motion vector/confidence value/occlusion detection分类
信息技术与安全科学引用本文复制引用
罗会兰,张文赛,钟睿,孔繁胜..结合运动矢量的分权快速压缩跟踪算法[J].中南大学学报（自然科学版）,2017,48(2):395-403,9.基金项目
国家自然科学基金资助项目(61462035) （61462035）
江西省青年科学家培养项目(20153BCB23010)(Project(61462035) supported by the National Natural Science Foundation of China （20153BCB23010）
Project(20153BCB23010) supported by Young Scientist Training Project of Jiangxi Province) （20153BCB23010）
