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Feature Aggregation With Reinforcement Learning for Video-Based Person Re-Identification
Zhang, Wei1; He, Xuanyu1; Lu, Weizhi1; Qiao, Hong2; Li, Yibin1
Source PublicationIEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
ISSN2162-237X
2019-12-01
Volume30Issue:12Pages:3847-3852
Corresponding AuthorHe, Xuanyu(hexiffer@outlook.com)
AbstractVideo-based person re-identification (re-id) matches two tracks of persons from different cameras. Features are extracted from the images of a sequence and then aggregated as a track feature. Compared to existing works that aggregate frame features by simply averaging them or using temporal models such as recurrent neural networks, we propose an intelligent feature aggregate method based on reinforcement learning. Specifically, we train an agent to determine which frames in the sequence should be abandoned in the aggregation, which can be treated as a decision making process. By this way, the proposed method avoids introducing noisy information of the sequence and retains these valuable frames when generating a track feature. On benchmark data sets, experimental results show that our method can boost the re-id accuracy obviously based on the state-of-the-art models.
KeywordFeature extraction Task analysis Cameras Noise measurement Learning systems Reinforcement learning Feature aggregation reinforcement learning (RL) sequential decision making video-based person re-identification (re-id)
DOI10.1109/TNNLS.2019.2899588
Indexed BySCI
Language英语
Funding ProjectNational Key Research and Development Plan of China[2017YFB1300205] ; NSFC[61573222] ; NSFC[61801264] ; Major Research Program of Shandong Province[2018CXGC1503] ; Fundamental Research Funds of Shandong University[2016JC014] ; Basic Research Program of Shenzhen[JCYJ20170307153635551] ; National Key Research and Development Plan of China[2017YFB1300205] ; NSFC[61573222] ; NSFC[61801264] ; Major Research Program of Shandong Province[2018CXGC1503] ; Fundamental Research Funds of Shandong University[2016JC014] ; Basic Research Program of Shenzhen[JCYJ20170307153635551]
Funding OrganizationNational Key Research and Development Plan of China ; NSFC ; Major Research Program of Shandong Province ; Fundamental Research Funds of Shandong University ; Basic Research Program of Shenzhen
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000502762600028
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/29440
Collection中国科学院自动化研究所
Corresponding AuthorHe, Xuanyu
Affiliation1.Shandong Univ, Sch Control Sci & Engn, Jinan 250100, Shandong, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Wei,He, Xuanyu,Lu, Weizhi,et al. Feature Aggregation With Reinforcement Learning for Video-Based Person Re-Identification[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2019,30(12):3847-3852.
APA Zhang, Wei,He, Xuanyu,Lu, Weizhi,Qiao, Hong,&Li, Yibin.(2019).Feature Aggregation With Reinforcement Learning for Video-Based Person Re-Identification.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,30(12),3847-3852.
MLA Zhang, Wei,et al."Feature Aggregation With Reinforcement Learning for Video-Based Person Re-Identification".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 30.12(2019):3847-3852.
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