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  • Research Article
  • Open Access

Better Flow Estimation from Color Images

EURASIP Journal on Advances in Signal Processing20072007:053912

  • Received: 1 October 2006
  • Accepted: 20 March 2007
  • Published:


One of the difficulties in estimating optical flow is bias. Correcting the bias using the classical techniques is very difficult. The reason is that knowledge of the error statistics is required, which usually cannot be obtained because of lack of data. In this paper, we present an approach which utilizes color information. Color images do not provide more geometric information than monochromatic images to the estimation of optic flow. They do, however, contain additional statistical information. By utilizing the technique of instrumental variables, bias from multiple noise sources can be robustly corrected without computing the parameters of the noise distribution. Experiments on synthesized and real data demonstrate the efficiency of the algorithm.


  • Information Technology
  • Real Data
  • Error Statistic
  • Statistical Information
  • Quantum Information

Authors’ Affiliations

Department of Mathematics, National University of Singapore, 117543, Singapore
Computer Vision Laboratory, Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20742-3275, USA


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© H. Ji and C. Fermüller. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.