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

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

研究成果: 書貢獻/報告類型會議論文篇章

11 引文 斯高帕斯(Scopus)

摘要

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.

原文英語
主出版物標題2013 IEEE International Conference on Multimedia and Expo, ICME 2013
DOIs
出版狀態已發佈 - 2013
對外發佈
事件2013 IEEE International Conference on Multimedia and Expo, ICME 2013 - San Jose, CA, 美国
持續時間: 2013 七月 152013 七月 19

出版系列

名字Proceedings - IEEE International Conference on Multimedia and Expo
ISSN(列印)1945-7871
ISSN(電子)1945-788X

其他

其他2013 IEEE International Conference on Multimedia and Expo, ICME 2013
國家/地區美国
城市San Jose, CA
期間2013/07/152013/07/19

ASJC Scopus subject areas

  • 電腦網路與通信
  • 電腦科學應用

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