Binocular video object tracking with fast disparity estimation

Yun Ye, Song Ci, Yanwei Liu, Haohong Wang, Aggelos K. Katsaggelos

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

4 Scopus citations

Abstract

This paper presents a binocular PTU (pan-tilt unit) camera video object tracking scheme using the MeanShift algorithm and the runtime disparity estimation. The proposed method is to accommodate the requirement of 3D content generation and accurate tracking in more advanced video surveillance applications. The disparity estimation process for each stereoscopic pair is formulated as an energy minimization problem. The iterative solution procedure is implemented in a course-to-fine manner. The estimated disparity is used to scale the tracking window by the MeanShift algorithm, i.e. the size of the tracking area is adjustable according to its inner disparity, and thus the moving object can be better located by the camera. The program maintains the semi-real-time performance and acceptable accuracy as evaluated on a set of standard test data. In our experiment, two PointGrey cameras are controlled through a PTU device. The disparity estimation process on the recorded tracking video (640×480) achieves 6fps on an ordinary PC (2.66GHz CPU, 4GB RAM).

Original languageEnglish (US)
Title of host publication2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2013
PublisherIEEE Computer Society
Pages183-188
Number of pages6
ISBN (Print)9781479907038
DOIs
StatePublished - 2013
Event2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2013 - Krakow, Poland
Duration: Aug 27 2013Aug 30 2013

Publication series

Name2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2013

Other

Other2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2013
CountryPoland
CityKrakow
Period8/27/138/30/13

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

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