Open Access
Issue
JNWPU
Volume 37, Number 5, October 2019
Page(s) 1070 - 1076
DOI https://doi.org/10.1051/jnwpu/20193751070
Published online 14 January 2020
  1. Cai Q, Aggarwal J K. Tracking Human Motion Using Multiple Cameras[C]//International Conference on Pattern Recognition, 1996: 68–72 [Article] [Google Scholar]
  2. Gheissari N, Sebastian T B. Person Reidentification using Spatiotemporal Appearance[C]//Computer Vision and Pattern Recognition, 2016: 1528–1535 [Article] [Google Scholar]
  3. Weinberger K Q, Saul L K. Distance Metric Learning for Large Margin Nearest Neighbor Classification[J]. Journal of Machine Learning Research, 2009, 10(1): 207–244 [Article] [Google Scholar]
  4. Zheng W S, Gong S, Xiang T. Person Re-Identification by Probabilistic Relative Distance Comparison[C]//Computer Vision and Pattern Recognition, 2011: 649–656 [Article] [Google Scholar]
  5. Li A, Liu L, Yan S. Person Re-Identification by Attribute-Assisted Clothes Appearance[M]. Springer London, Person Re-Identification, 2014: 119–138 [Google Scholar]
  6. Varior R R, Shuai B, Lu J, et al. A Siamese Long Short-Term Memory Architecture for Human Re-Identification[J]. European Conference on Computer Vision, 2016, 135–153 [Article] [Google Scholar]
  7. Zheng L, Huang Y, Lu H, et al. Pose Invariant Embedding for Deep Person Re-Identification[J]. Computer Vision and Pattern Recognition, 2017 [Article] [Google Scholar]
  8. Zhao L, Li X, Wang J, et al. Deeply-Learned Part-Aligned Representations for Person Re-identification[J]. Computer Vision and Pattern Recognition, 2017, 1: 3239–3248 [Article] [Google Scholar]
  9. Wei L, Zhang S, Yao H, et al. GLAD:Global-Local-Alignment Descriptor for Pedestrian Retrieval[J]. Computer Vision and Pattern Recognition, 2017 [Article] [Google Scholar]
  10. Zhao H, Tian M, Sun S, et al. Spindle Net: Person Re-Identification with Human Body Region Guided Feature Decomposition and Fusion[C]//Computer Vision and Pattern Recognition, 2017, 1: 907–915 [Article] [Google Scholar]
  11. Zhang K, Zhang Z, Li Z, et al. Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks[J]. IEEE Signal Processing Letters, 2016, 23(10): 1499–1503 [Article] [NASA ADS] [CrossRef] [Google Scholar]
  12. Wei S E, Ramakrishna V, Kanade T, et al. Convolutional Pose Machines[J]. Computer Vision and Pattern Recognition, 2016, 4724–4732 [Article] [Google Scholar]
  13. Li W, Zhao R, Wang X, et al. Human Reidentification with Transferred Metric Learning[C]//Asian Conference on Computer Vision, 2012: 31–44 [Article] [Google Scholar]
  14. Li W, Zhao R, Xiao T, et al. DeepReID: Deep Filter Pairing Neural Network for Person Re-Identification[C]//2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014: 152–159 [Article] [Google Scholar]
  15. Gray D, Tao H. Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features[C]//European Conference on Computer Vision, 2008: 262–275 [Article] [Google Scholar]
  16. Hirzer M, Beleznai C, Roth P M, et al. Person Re-Identification by Descriptive and Discriminative Classification[C]//Scandinavian Conference on Image Analysis, 2011: 91–102 [Article] [Google Scholar]
  17. Wang T, Gong S, Zhu X, et al. Person Re-Identification by Video Ranking[C]//European Conference on Computer Vision, 2014: 688–703 [Article] [Google Scholar]
  18. Baltieri, Davide, et al. 3DPeS: 3D People Dataset for Surveillance and Forensics[C]//Proceedings of the 2011 Joint ACM Workshop on Human Gesture and Behavior Understanding, 2011: 59–64 [Article] [Google Scholar]
  19. Decann B, Ross A. Relating ROC and CMC Curves via the Biometric Menagerie[C]//IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems, 2013: 1–8 [Article] [Google Scholar]

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