Person reidentification using spatiotemporal appearance

Niloofar Gheissari*, Thomas B. Sebastian, Peter H. Tu, Jens Rittscher, Richard Hartley

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    553 Citations (Scopus)

    Abstract

    In many surveillance applications it is desirable to determine if a given individual has been previously observed over a network of cameras. This is the person reidentification problem. This paper focuses on reidentification algorithms that use the overall appearance of an individual as opposed to passive biometrics such as face and gait. Person reidentification approaches have two aspects: (i) establish correspondence between parts, and (ii) generate signatures that are invariant to variations in illumination, pose, and the dynamic appearance of clothing. A novel spatiotemporal segmentation algorithm is employed to generate salient edgels that are robust to changes in appearance of clothing. The invariant signatures are generated by combining normalized color and salient edgel histograms. Two approaches are proposed to generate correspondences: (i) a model based approach that fits an articulated model to each individual to establish a correspondence map, and (ii) an interest point operator approach that nominates a large number of potential correspondences which are evaluated using a region growing scheme. Finally, the approaches are evaluated on a 44 person database across 3 disparate views.

    Original languageEnglish
    Title of host publicationProceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006
    Pages1528-1535
    Number of pages8
    DOIs
    Publication statusPublished - 2006
    Event2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006 - New York, NY, United States
    Duration: 17 Jun 200622 Jun 2006

    Publication series

    NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
    Volume2
    ISSN (Print)1063-6919

    Conference

    Conference2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006
    Country/TerritoryUnited States
    CityNew York, NY
    Period17/06/0622/06/06

    Fingerprint

    Dive into the research topics of 'Person reidentification using spatiotemporal appearance'. Together they form a unique fingerprint.

    Cite this