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Estimate Large Motions Using the Reliability-Based Motion Estimation Algorithm

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Abstract

Detecting and estimating motions of fast moving objects has many important applications. However, most existing motion estimation techniques have difficulties in handling large motions in the scene. In this paper, we extend our recently proposed reliability-based stereo vision technique to solving large motion estimation problem. Compared with our stereo vision approach, the new algorithm removes the constant penalty assumption and explicitly enforces the inter-scanline consistency constraint. The resulting algorithm can handle sequences that contain large motions and can produce optical flows with 100% density over the entire image domain. The experimental results indicate that it can generate more accurate optical flows than existing approaches.

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Authors and Affiliations

  1. Department of Math and Computer Science, Laurentian University, Sudbury, ON, Canada

    Minglun Gong

  2. Department of Computing Science, University of Alberta, Edmonton, AB, Canada

    Yee-Hong Yang

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  1. Minglun Gong
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  2. Yee-Hong Yang
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Correspondence to Minglun Gong.

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Gong, M., Yang, YH. Estimate Large Motions Using the Reliability-Based Motion Estimation Algorithm. Int J Comput Vision 68, 319–330 (2006). https://doi.org/10.1007/s11263-006-5099-x

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  • DOI: https://doi.org/10.1007/s11263-006-5099-x

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