Cross-camera vehicle tracking via affine invariant object matching for video forensics applications

Chao Yung Hsu, Li Wei Kang, Hong Yuan Mark Liao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect and track each vehicle within a large area, which can be applied to video forensics. For example, a suspected vehicle can be automatically identified for mining digital criminal evidences from a large amount of video data. In this paper, we propose an efficient cross-camera vehicle tracking technique via affine invariant object matching. More specifically, we formulate the problem as invariant image feature matching among different viewpoints of cameras. To achieve vehicle matching, we first extract invariant image feature based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, to improve the accuracy of ASIFT feature matching between images from different viewpoints, we propose to efficiently match feature points based on our observed spatially invariant property of ASIFT, as well as the min-hash technique. As a result, cross-camera vehicle tracking can be efficiently and accurately achieved. Experimental results demonstrate the efficacy of the proposed algorithm and the feasibility to video forensics applications.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Multimedia and Expo, ICME 2013
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 IEEE International Conference on Multimedia and Expo, ICME 2013 - San Jose, CA, United States
Duration: 2013 Jul 152013 Jul 19

Publication series

NameProceedings - IEEE International Conference on Multimedia and Expo
ISSN (Print)1945-7871
ISSN (Electronic)1945-788X

Other

Other2013 IEEE International Conference on Multimedia and Expo, ICME 2013
Country/TerritoryUnited States
CitySan Jose, CA
Period2013/07/152013/07/19

Keywords

  • Affine SIFT
  • Camera networks
  • Object matching
  • Vehicle tracking
  • video forensics
  • Video surveillance

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

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