基于局部突出性稠密块匹配的人体重现

doi:10.3969/j.issn.1000-3428.2016.06.048

摘要/Abstract

摘要： 人体重现是人体目标提取及跟踪中的关键技术,目前多数方法都是通过提取人体表观特征并计算特征相似度来实现人体匹配,对表观特征差异较大的图像识别准确率较高,但不适用于表观特征相似的图像。考虑到同一行人不同图像的表观特征局部结构信息比不同行人相似图像表现得更相似,提出一种基于局部突出性稠密块匹配的人体重现算法。提取每个稠密块的组合特征,计算每块在局部区域里的相似性,并据此确定其在局部区域里的突出权重。在VIPeR和CUHK数据库上的实验结果表明,该方法识别率较高,对视觉、姿势和光照的变化具有强鲁棒性,并且对多数表观特征相似的行人也能给出准确的匹配结果。

关键词: 人体重现, 目标提取, 表观特征, 局部结构信息, 稠密块匹配, 局部突出性

Abstract: Person re-identification is the key technology in human object extraction and tracking.Now,mostly person re-identification methods extract the human appearance feature and compute the feature similarity to implement the human matching.These methods can get accurate results for the images which have apparent differnce,but they are difficult to recognize images which have similar areas.Aiming at this problem,considering the region structure informations of the appearance feature in the different images of the same pedestrian are more similar than that in the similar images of different pedestrians,this paper proposes a person re-identification algorithm based on dense patch matching with local saliency.It extracts the combination feature of each dense block,calculates the similarity of each block in the local area and its saliency weight in local region according to the similarity.Experimental results on the VIPeR dataset and the CUHK dataset show that the proposed algorithm has higher recognition rate.It is invariant to the effects of variations of viewpoints,poses,lightings,and it can provide accurate matching results of pedestrians who have the most similar areas.

Key words: person re-identification, object extraction, appearance feature, local structure information, dense patch matching, local saliency

中图分类号:

TP391

柯伟扬,郭立君,张荣,王亚东. 基于局部突出性稠密块匹配的人体重现[J]. 计算机工程, doi: 10.3969/j.issn.1000-3428.2016.06.048.

KE Weiyang,GUO Lijun,ZHANG Rong,WANG Yadong. Person Re-identification Based on Dense Patch Matching with Local Saliency[J]. Computer Engineering, doi: 10.3969/j.issn.1000-3428.2016.06.048.

https://www.ecice06.com/CN/Y2016/V42/I6/274

参考文献

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