Person re-identification

구글에서 걍 검색. 2013년 이후 인용 75 이상인것들.

Mahalanobis distance learning for person re-identification

PM Roth, M Hirzer, M Köstinger, C Beleznai… - … Re-Identification, 2014 - Springer [1] Gong의 책중 한 챕터

Unsupervised salience learning for person re-identification

R Zhao, W Ouyang, X Wang - Proceedings of the IEEE …, 2013 - cv-foundation.org [2]

github

Learning mid-level filters for person re-identification

• R Zhao, W Ouyang, X Wang - Proceedings of the IEEE …, 2014 - cv-foundation.org [3]

Deepreid: Deep filter pairing neural network for person re-identification

• W Li, R Zhao, T Xiao, X Wang - Proceedings of the IEEE …, 2014 - cv-foundation.org [4]

Person re-identification by LOMO(local maximal occurrence) representation and metric learning

• S Liao, Y Hu, X Zhu, SZ Li - … of the IEEE Conference on Computer …, 2015 - cv-foundation.org [5]
• Retinex algorithm

  Retinex considers human lightness and color perception. It aims at producing a color image that is consistent to human observation of the scene. The restored image usually contains vivid color in- formation, especially enhanced details in shadowed regions.

  • multi-scale Retinex algorithm
• SILTP

  we also apply the Scale Invariant Local Ternary Pattern (SILTP) [26] descriptor for illumination invariant texture description. SILTP is an im- proved operator over the well-known Local Binary Pattern (LBP) [37]. In fact, LBP has a nice invariant property un- der monotonic gray-scale transforms, but it is not robust to image noises. SILTP improves LBP by introducing a scale invariant local comparison tolerance, achieving invariance to intensity scale changes and robustness to image noises.

• Bayesian face

  learning the distance function corresponds to estimating the covariant matrices \(\Sigma_I\) and \(\Sigma_E\).

  • I : interpersonal , E : extrapersonal. I : 같은 label의 \(\delta\)x, E : 다른 label의 \(\delta\)x.
• Fisher criterion [6]

  Fisher criterion is a discriminant criterion function that was first presented by Fisher in 1936. It is defined by the ratio of the between-class scatter to the within-class scatter. By maximizing this criterion, one can obtain an optimal discriminant projection axis. After the sample being projected on to this projection axis, the within-class scatter is minimized and the between-class scatter is maximized.

  • \(\large S = \frac{\sigma^2_\text{between}}{\sigma^2_\text{within}} \) 즉, 크면 클수록 구분을 잘 하는 것이다.
  • LDA가 이것의 일반화 [7]
    • Fisher의 original article에 normally distributed classes 와 equal class covariances 가정을 더하면 LDA [8]

Person re-identification using kernel-based metric learning methods

• F Xiong, M Gou, O Camps, M Sznaier - European conference on computer …, 2014 - Springer [9]

Salient color names for person re-identification

• Y Yang, J Yang, J Yan, S Liao, D Yi, SZ Li - European Conference on …, 2014 - Springer [10]

An improved deep learning architecture for person re-identification

• E Ahmed, M Jones, TK Marks - Proceedings of the IEEE …, 2015 - cv-foundation.org [11]
• github

Person re-identification by salience matching

• R Zhao, W Ouyang, X Wang - Proceedings of the IEEE …, 2013 - cv-foundation.org [12]

Deep metric learning for person re-identification

• D Yi, Z Lei, S Liao, SZ Li - Pattern Recognition (ICPR), 2014 …, 2014 - ieeexplore.ieee.org [13]

A survey of approaches and trends in person re-identification

• A Bedagkar-Gala, SK Shah - Image and Vision Computing, 2014 - Elsevier [14]

Person re-identification by video ranking

• T Wang, S Gong, X Zhu, S Wang - European Conference on Computer …, 2014 - Springer [15]

Learning to rank in person re-identification with metric ensembles

• S Paisitkriangkrai, C Shen… - Proceedings of the IEEE …, 2015 - cv-foundation.org [16]

Learning a discriminative null space for person re-identification

• L Zhang, T Xiang, S Gong - … of the IEEE Conference on Computer …, 2016 - cv-foundation.org
• cited by 44
• pdf and code Li Zhang’s page

Learning deep feature representations with domain guided dropout for person re-identification

• T Xiao, H Li, W Ouyang, X Wang - Proceedings of the IEEE …, 2016 - cv-foundation.org [17]
• github
• cited by 39

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