A unified hierarchical appearance model for people re-identification using multi-view vision sensors

Jau Hong Kao, Chih Yang Lin, Wen How Wang, Yi Ta Wu

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

7 Scopus citations

Abstract

Surveillance of wide areas requires a system of multiple cameras to keep observing people. In such a multiple view system, the people appearance obtained in one camera is usually different from the ones obtained in other cameras. In order to correctly identify people, the unique appearance model of each specific object should be invariant to such changes. In this paper, our appearance model is represented by a hierarchical structure where each node maintains a color Gaussian mixture model (GMM). The re-identification is performed with Bayesian decision. Experimental results show our unified appearance model is robust to rotation and scaling variations. Furthermore, it achieves high accuracy rate (92.7% in average) and high processing performance (above 30 FPS) without tracking mechanism.

Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing - PCM 2008 - 9th Pacific Rim Conference on Multimedia, Proceedings
Pages553-562
Number of pages10
DOIs
StatePublished - 2008
Event9th Pacific Rim Conference on Multimedia, PCM 2008 - Tainan, Taiwan
Duration: 9 Dec 200813 Dec 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5353 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th Pacific Rim Conference on Multimedia, PCM 2008
Country/TerritoryTaiwan
CityTainan
Period9/12/0813/12/08

Keywords

  • Appearance model
  • GMM
  • Invariants
  • Multiple-view
  • Re-identification
  • Tracking

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