电子学报2017，Vol.45Issue(4)：799-804,6.DOI:10.3969/j.issn.0372-2112
基于自适应分层结构的压缩分布场跟踪算法
Object Tracking by Compressive Distribution Fields with Adaptive Hierarchical Structure
摘要
Abstract
In order to improve the efficiency of tracking algorithm based on distribution fields and the robustness of the algorithm under complex background,tracking algorithm by compressive distribution fields with adaptive hierarchical structure is presented.Distribution of pixel values in target region is considered in this method,k-means algorithm is introduced to analyse the distribution of pixel values in the first frame,adaptive hierarchical structure of distribution fields is built according to the clustering results.For the problem that the dimension of distribution field model is high,compressive sensing is combined to compress distribution fields,which can reduce the model dimension and improve the efficiency of tracking algorithm.Furthermore,local search strategy in original distribution fields tracking algorithm is changed,random sampling is used to improve the tracking accuracy.Experimental results demonstrate that the proposed algorithm outperforms the state-of-the-art tracking algorithms.关键词
分布场/压缩感知/目标跟踪/聚类分析Key words
distribution fields/compressive sensing/object tracking/cluster analysis分类
信息技术与安全科学引用本文复制引用
王亚文,陈鸿昶,李邵梅,高超..基于自适应分层结构的压缩分布场跟踪算法[J].电子学报,2017,45(4):799-804,6.基金项目
国家自然科学基金(No.61379151,No.61521003) （No.61379151,No.61521003）
国家科技支撑计划(No.2014BAH30B01) （No.2014BAH30B01）
河南省杰出青年基金(No.144100510001) （No.144100510001）
