Domain transfer support vector ranking for person re-identification without target camera label information

Andy J. Ma, Pong Chi YUEN, Jiawei Li

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

78 Citations (Scopus)

Abstract

This paper addresses a new person re-identification problem without the label information of persons under non-overlapping target cameras. Given the matched (positive) and unmatched (negative) image pairs from source domain cameras, as well as unmatched (negative) image pairs which can be easily generated from target domain cameras, we propose a Domain Transfer Ranked Support Vector Machines (DTRSVM) method for re-identification under target domain cameras. To overcome the problems introduced due to the absence of matched (positive) image pairs in target domain, we relax the discriminative constraint to a necessary condition only relying on the positive mean in target domain. By estimating the target positive mean using source and target domain data, a new discriminative model with high confidence in target positive mean and low confidence in target negative image pairs is developed. Since the necessary condition may not truly preserve the discriminability, multi-task support vector ranking is proposed to incorporate the training data from source domain with label information. Experimental results show that the proposed DTRSVM outperforms existing methods without using label information in target cameras. And the top 30 rank accuracy can be improved by the proposed method upto 9.40% on publicly available person re-identification datasets.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE International Conference on Computer Vision, ICCV 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3567-3574
Number of pages8
ISBN (Print)9781479928392
DOIs
Publication statusPublished - 2013
Event2013 14th IEEE International Conference on Computer Vision, ICCV 2013 - Sydney, NSW, Australia
Duration: 1 Dec 20138 Dec 2013

Publication series

NameProceedings of the IEEE International Conference on Computer Vision

Conference

Conference2013 14th IEEE International Conference on Computer Vision, ICCV 2013
Country/TerritoryAustralia
CitySydney, NSW
Period1/12/138/12/13

Scopus Subject Areas

  • Software
  • Computer Vision and Pattern Recognition

User-Defined Keywords

  • Domain Adaptation
  • Person Re-Identification

Fingerprint

Dive into the research topics of 'Domain transfer support vector ranking for person re-identification without target camera label information'. Together they form a unique fingerprint.

Cite this