Knowledge Commons of Institute of Automation,CAS
Part-based Structured Representation Learning for Person Re-identification | |
Li, Yaoyu1,2; Yao, Hantao1,2; Zhang, Tianzhu3; Xu, Changsheng1,2,4 | |
发表期刊 | ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS |
ISSN | 1551-6857 |
2020-12-01 | |
卷号 | 16期号:4页码:22 |
摘要 | Person re-identification aims to match person of interest under non-overlapping camera views. Therefore, how to generate a robust and discriminative representation is crucial for person re-identification. Mining local clues from human body parts to describe pedestrians has been extensively studied in existing methods. However, existing methods locate human body parts coarsely and do not consider the relations among different local parts. To address the above problem, we propose a Part-based Structured Representation Learning (PSRL) for better exploiting local clues to improve the person representation. There are two important modules in our architecture: Local Semantic Feature Extraction and Structured Person Representation Learning. The Local Semantic Feature Extraction module is designed to extract local features from human body semantic regions. After obtaining the local features, the Structured Person Representation Learning is proposed to fuse the local features by considering the person structure. To model the underlying person structure, a graph convolutional network is employed to capture the relations of different semantic regions. The generated structured feature encodes underlying person structure information, and local semantic feature can solve the misalignment problem caused by pose variations in feature matching. By combining them together, we can improve the descriptive ability of the generated representation. Extensive evaluations on four standard benchmarks show that our proposed method achieves competitive performance against state-of-the-art methods. |
关键词 | Person re-identification representation learning graph convolutional network |
DOI | 10.1145/3412384 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2018AAA0102200] ; National Natural Science Foundation of China[61902399] ; National Natural Science Foundation of China[61721004] ; National Natural Science Foundation of China[U1705262] ; National Natural Science Foundation of China[61532009] ; National Natural Science Foundation of China[61832002] ; National Natural Science Foundation of China[61720106006] ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-JSC039] ; National Postdoctoral Programme for Innovative Talents[BX20180358] |
项目资助者 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Key Research Program of Frontier Sciences, CAS ; National Postdoctoral Programme for Innovative Talents |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods |
WOS记录号 | WOS:000614096700018 |
出版者 | ASSOC COMPUTING MACHINERY |
七大方向——子方向分类 | 图像视频处理与分析 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/42862 |
专题 | 多模态人工智能系统全国重点实验室_多媒体计算 |
通讯作者 | Xu, Changsheng |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, 95 Zhongguancun East Rd, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, 95 Zhongguancun East Rd, Beijing, Peoples R China 3.Univ Sci & Technol China, 1202 Room Sci & Technol West Bldg,Huangshan Rd, Hefei, Anhui, Peoples R China 4.Peng Cheng Lab, Shenzhen, Peoples R China |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Li, Yaoyu,Yao, Hantao,Zhang, Tianzhu,et al. Part-based Structured Representation Learning for Person Re-identification[J]. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,2020,16(4):22. |
APA | Li, Yaoyu,Yao, Hantao,Zhang, Tianzhu,&Xu, Changsheng.(2020).Part-based Structured Representation Learning for Person Re-identification.ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,16(4),22. |
MLA | Li, Yaoyu,et al."Part-based Structured Representation Learning for Person Re-identification".ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 16.4(2020):22. |
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