Person re-identification by Local Maximal Occurrence representation and metric learning
- 1 June 2015
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 2197-2206
- https://doi.org/10.1109/cvpr.2015.7298832
Abstract
Person re-identification is an important technique towards automatic search of a person's presence in a surveillance video. Two fundamental problems are critical for person re-identification, feature representation and metric learning. An effective feature representation should be robust to illumination and viewpoint changes, and a discriminant metric should be learned to match various person images. In this paper, we propose an effective feature representation called Local Maximal Occurrence (LOMO), and a subspace and metric learning method called Cross-view Quadratic Discriminant Analysis (XQDA). The LOMO feature analyzes the horizontal occurrence of local features, and maximizes the occurrence to make a stable representation against viewpoint changes. Besides, to handle illumination variations, we apply the Retinex transform and a scale invariant texture operator. To learn a discriminant metric, we propose to learn a discriminant low dimensional subspace by cross-view quadratic discriminant analysis, and simultaneously, a QDA metric is learned on the derived subspace. We also present a practical computation method for XQDA, as well as its regularization. Experiments on four challenging person re-identification databases, VIPeR, QMUL GRID, CUHK Campus, and CUHK03, show that the proposed method improves the state-of-the-art rank-1 identification rates by 2.2%, 4.88%, 28.91%, and 31.55% on the four databases, respectively.Keywords
Other Versions
This publication has 37 references indexed in Scilit:
- Covariance descriptor based on bio-inspired features for person re-identification and face verificationImage and Vision Computing, 2014
- Video Text DetectionPublished by Springer Science and Business Media LLC ,2014
- Person re-identification by manifold rankingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- Local Fisher Discriminant Analysis for Pedestrian Re-identificationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- Person re-identification based on visual saliencyPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2012
- PCCA: A new approach for distance learning from sparse pairwise constraintsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2012
- Person Re-identification: What Features Are Important?Lecture Notes in Computer Science, 2012
- Person Re-Identification by Support Vector RankingPublished by British Machine Vision Association and Society for Pattern Recognition ,2010
- Bayesian face recognitionPattern Recognition, 2000
- A comparative study of texture measures with classification based on featured distributionsPattern Recognition, 1996