Person Re Identification By Support Vector Ranking

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(PDF) Person Re-Identification by Support Vector Ranking

    https://www.researchgate.net/publication/221259651_Person_Re-Identification_by_Support_Vector_Ranking
    Person re-identification (re-ID) is a challenging task since the same person captured by different cameras can appear very differently, due to the uncontrolled factors such as occlusion ...

Person Re-Identification by Support Vector Ranking

    https://www.researchgate.net/profile/Shaogang_Gong/publication/221259651_Person_Re-Identification_by_Support_Vector_Ranking/links/54f858b20cf2ccffe9de969e/Person-Re-Identification-by-Support-Vector-Ranking.pdf
    PROSSERet al.: PERSON RE-IDENTIFICATION BY SUPPORT VECTOR RANKING 3 to a relative ranking problem. We thus avoid the need for seeking a maximum distance score

CiteSeerX — Person reidentification by support vector ranking

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.309.6600
    The novelty of this work is that we reformulate the person reidentification problem as a ranking problem and learn a subspace where the potential true match is given highest ranking rather than any direct distance measure. By doing so, we convert the person re-identification problem from an absolute scoring problem to a relative ranking problem.

Domain Transfer Support Vector Ranking for Person Re ...

    http://www.stat.rutgers.edu/home/jma/publications/DTPRID_final.pdf
    Domain Transfer Support Vector Ranking for Person Re-Identification without Target Camera Label Information Andy J Ma 1Pong C Yuen;2 Jiawei Li 1Department of Computer Science, Hong Kong Baptist University, Hong Kong 2BNU-HKBU United International College, Zhuhai, China fjhma, pcyuen, [email protected] Abstract

Person Re-identification based on nonlinear ranking with ...

    https://www.sciencedirect.com/science/article/pii/S0020025514004617
    Sep 20, 2014 · We then achieve re-identification through a ranking approach by employing a support vector machine with a nonlinear kernel based on radial basis function. We also propose to pre-cluster the training images using the affinity propagation clustering algorithm, and select representative images to form negative training instances.Cited by: 9

Person Re-Identification by Support Vector Ranking

    http://www.bmva.org/bmvc/2010/conference/paper21/index.html
    Person Re-Identification by Support Vector Ranking. In Frédéric Labrosse, Reyer Zwiggelaar, Yonghuai Liu, and Bernie Tiddeman, editors, Proceedings of the British Machine Vision Conference , pages 21.1-21.11.

Person Re-identification by Descriptive and Discriminative ...

    https://link.springer.com/chapter/10.1007/978-3-642-21227-7_9
    Person re-identification, i.e., recognizing a single person across spatially disjoint cameras, is an important task in visual surveillance. Existing approaches either try to find a suitable description of the appearance or learn a discriminative model.Cited by: 691

wangzwhu.github.io

    https://wangzwhu.github.io/home/re_id_resources.html
    Person Re-Identification by Support Vector Ranking . SDALF. CVPR'10. Person Re-identification by Symmetry-driven Accumulation of Local Features. Project. Code. CAVIAR4REID. BMVC'11. Custom pictorial structures for re-identification. Project . PRID 2011. SCIA'11. Person Re-Identification by Descriptive and Discriminative Classification. Project ...

A Pose-Sensitive Embedding for Person Re-Identification ...

    http://openaccess.thecvf.com/content_cvpr_2018/papers/Sarfraz_A_Pose-Sensitive_Embedding_CVPR_2018_paper.pdf
    A Pose-Sensitive Embedding for Person Re-Identification with Expanded Cross Neighborhood Re-Ranking M. Saquib Sarfraz1, Arne Schumann2,1, Andreas Eberle1, Rainer Stiefelhagen1 1Karlsruhe Institute of Technology, 2Fraunhofer IOSB Karlsruhe, Germany {firstname.lastname}@kit.eduCited by: 103

Person re-identification with block sparse recovery ...

    https://www.sciencedirect.com/science/article/abs/pii/S0262885616302050
    Furthermore, under certain conditions, the associated coefficient vector can be characterized as being block sparse. This key insight allows us to design an algorithm based on block sparse recovery that achieves state-of-the-art results in multi-shot person re-identification.



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