Video person re-identification using key frame screening with index and feature reorganization based on inter-frame relation-Reference-Cited by-同舟云学术

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Video person re-identification using key frame screening with index and feature reorganization based on inter-frame relation

Published:2022-04-19 Issue:9 Volume:13 Page:2745-2761
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Lu Zeng,Zhang Ganghan,Huang Guoheng^ORCID,Yu Zhiwen,Pun Chi-Man,Zhang Weiwen,Chen Junan,Ling Wing-Kuen

Funder

Key-area research and development program of guangdong province

Guangzhou r&d programne in the key area of science and technology projects

Guangdong provincial key laboratory of cyber-physical system

Program of Marine Economy Development (Six Marine Industries) Special Foundation of Department of Natural Resources of Guangdong Province

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s13042-022-01560-4.pdf

Reference58 articles.

1. Zhang W, Ma B, Liu K, Huang R (2017) Video-based pedestrian re-identification by adaptive spatio-temporal appearance model. IEEE Trans Image Process 26(4):2042–2054

2. Bay H, Ess A, Tuytelaars T, Van Gool L (2008) Speeded-up robust features (surf). Comput Vis Image Underst 110(3):346–359

3. Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: 2005 IEEE computer society conference on computer vision and pattern recognition (CVPR’05), vol 1. Ieee, pp. 886–893

4. Chaudhry R, Ravichandran A, Hager G, Vidal R (2009) Histograms of oriented optical flow and Binet–Cauchy kernels on nonlinear dynamical systems for the recognition of human actions. In: 2009 IEEE conference on computer vision and pattern recognition. IEEE, pp 1932–1939

5. Wang H, Kläser A, Schmid C, Liu CL (2013) Dense trajectories and motion boundary descriptors for action recognition. Int J Comput Vis 103(1):60–79

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