光学精密工程2012，Vol.20Issue(2)：439-446,8.DOI:10.3788/OPE.20122002.0439
遮挡环境下采用在线Boosting的目标跟踪
On-line boosting based target tracking under occlusion
摘要
Abstract
A new on-line boosting algorithm based on sub-regional classifiers was presented to solve the problem that traditional on-line boosting based tracking algorithm often leads to drifting or failure due to the accumulated error during on-line updating under serious occlusions. Firstly, the feature pool was divided into a number of sub-regional feature pools to correspond to their sub-regional classifiers. Then, the sub-regional classifiers were selected adaptively into a strong classifier to eliminate the influence of occluded sub-regions on the target location when occlusions took place. Finally, the sub-regional feature pools were updated partly to solve the problem of accumulated error during online learning. The proposed algorithm was tested with variant video sequences and results show that proposed algorithm achieves exact tracking for the object occluded, and the average computing frame rate is 15 frame/s when the object scale is 36 pixel×40 pixel. In conclusion,the algorithm can satisfy the requirements of stability under occlusion as compared with the original on-line boosting algorithm.关键词
在线Boosting/目标跟踪/子区域分类器/抗遮挡Key words
on-line boosting/ target tracking/ sub-regional classifier/ anti-occlusion分类
信息技术与安全科学引用本文复制引用
颜佳,吴敏渊..遮挡环境下采用在线Boosting的目标跟踪[J].光学精密工程,2012,20(2):439-446,8.基金项目
国家自然科学基金面上项目(No.61072135) （No.61072135）
