Person re-identification in crowd
Pattern Recognition Letters
People reidentification in surveillance and forensics: A survey
ACM Computing Surveys (CSUR)
Editor's Choice Article: A survey of approaches and trends in person re-identification
Image and Vision Computing
Features accumulation on a multiple view oriented model for people re-identification
3DOR '13 Proceedings of the Sixth Eurographics Workshop on 3D Object Retrieval
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In this paper we present a comparative study of local features for the task of person (re) identification. A combination of state of the art interest point detectors and descriptors is evaluated. The experiments are performed on a novel dataset which we make publicly available for future research in this area. The results indicate that there are significant differences between the evaluated descriptors, with GLOH and SIFT outperforming both Shape Context and SURF descriptors. The evaluated interest point descriptors perform equally well, with a slight advantage for the Hessian-Laplace detector. The Harris-Affine and Hessian-Affine affine invariant region detectors do not provide any performance advantage and therefore do not justify their additional computational expense.