自动化学报2016，Vol.42Issue(9)：1421-1431,11.DOI:10.16383/j.aas.2016.c150603
结合特征筛选与二次定位的快速压缩跟踪算法
Fast Compressive Tracking Algorithm Combining Feature Selection with Secondary Localization
摘要
Abstract
As the traditional compressive tracking algorithm fails to track targets stably under occlusive condition and update model accurately, a fast tracking algorithm combining feature selection with secondary localization based on compressive tracking (FSSL-CT) is proposed. Firstly, compressive features are extracted from sub-regions partitioned from the global region, and the distributions of each compressive feature in positive and negative classes are estimated. Secondly, the classifier model is updated utilizing the method of adaptive learning rate and positive class update threshold. Finally, the tracking stage is divided into two procedures. In each procedure, some candidate samples are collected in the given searching region, and partial high quality features are selected from all the features and weighted to construct a classifier, then, the candidate samples are classified by the classifier. After that, the target tracking is achieved. Compared with two state-of-the-art algorithms on 8 public testing sequences and 4 private sequences, the FSSL-CT algorithm is proved to have the highest tracking success ratio and the lowest average central error in most of the sequences, and the average processing speed could achieve 3.04 milliseconds per frame. It is tested that the proposed FSSL-CT algorithm has a better capacity of resisting short-time occlusion and running in real-time, higher accuracy and robustness than the two state-of-the-art algorithms.关键词
压缩跟踪/特征筛选/二次定位/分布差异/自适应更新Key words
Compressive tracking/feature select/secondary localization/distribution difference/adaptive update引用本文复制引用
耿磊,王学彬,肖志涛,张芳,吴骏,李月龙,苏静静..结合特征筛选与二次定位的快速压缩跟踪算法[J].自动化学报,2016,42(9):1421-1431,11.基金项目
国家自然科学基金(61302127),高等学校博士学科点专项科研基金(20131201110001),天津市科技支撑计划重点项目(14ZCZDGX00033)资助Supported by National Natural Science Foundation of China (61302127), Specialized Research Fund for the Poctoral Pro-gram of Higher Education of China (20131201110001), Key Projects of Tianjin Science and Technology Support Program (14ZCZDGX00033) （61302127）
