基于协同表示的目标跟踪算法

doi:10.7523/j.issn.2095-6134.2016.01.020

中国科学院大学学报 ›› 2016, Vol. 33 ›› Issue (1): 135-143.DOI: 10.7523/j.issn.2095-6134.2016.01.020

• 信息与电子科学 • 上一篇

基于协同表示的目标跟踪算法

王海军, 张圣燕

滨州学院山东省高校航空信息技术重点实验室, 山东滨州 256603

收稿日期:2015-01-07 修回日期:2015-09-02 发布日期:2016-01-15
通讯作者: 王海军
基金资助:
山东省自然科学基金高校、科研单位联合专项计划项目(ZR2015FL009,ZR2014FL020)、滨州市科技发展计划项目(2013ZC0103)和滨州学院科研基金(BZXYG1524)资助

Algorithm of object-tracking based on collaborative representation

WANG Haijun, ZHANG Shengyan

Key Laboratory of Aviation Information Technology in University of Shandong, Binzhou University, Binzhou 256603, Shandong, China

Received:2015-01-07 Revised:2015-09-02 Published:2016-01-15

摘要/Abstract

摘要：

提出一种基于协同表示的新的目标跟踪算法.在贝叶斯框架下,采用基于重构误差的观测似然函数和考虑遮挡的模型更新机制设计一个鲁棒的跟踪器.用l₁范数来建模重构误差以更好地容忍奇异值,同时用协同表示对编码系数进行约束.实验结果表明,和其他算法相比,本文算法能够战胜遮挡、尺度变化、光照变化、背景混乱等干扰因素,具有较高的准确度和鲁棒性.

关键词: 目标跟踪, 协同表示, l₁范数, 观测似然函数

Abstract:

A new algorithm of object-tracking based on collaborative representation is proposed. Within Bayes framework,the robust tracker is presented using the observation likelihood model based on the error reconstruction and the updating scheme accounting for occlusion. The error reconstruction is modelled by the l₁ norm to tolerate the outlier, and the code coefficients are regularized by collaborative representation. Experimental results show that the proposed algorithm solves the problems of occlusion, scale changing, varying illumination, and cluttered background with high accuracy and robustness.

Key words: object tracking, collaborative representation, l₁ norm, observation likelihood function

中图分类号:

TP391

王海军, 张圣燕. 基于协同表示的目标跟踪算法[J]. 中国科学院大学学报, 2016, 33(1): 135-143.

WANG Haijun, ZHANG Shengyan. Algorithm of object-tracking based on collaborative representation[J]. , 2016, 33(1): 135-143.

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基于协同表示的目标跟踪算法

Algorithm of object-tracking based on collaborative representation

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