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Filtering Motion Vectors using an Adaptive Weight Function  

장석우 (한국건설기술연구원 건설CALS연구센터)
김진욱 (한국건설기술연구원 건설CALS연구센터)
이근수 (한경대학교 컴퓨터공학과)
김계영 (숭실대학교 컴퓨터학부)
Publication Information
Journal of KIISE:Software and Applications / v.31, no.11, 2004 , pp. 1474-1482 More about this Journal
Abstract
In this paper, we propose an approach for extracting and filtering block motion vectors using an adaptive weight function. We first extract motion vectors from a sequence of images by using size-varibale block matching and then process them by adaptive robust estimation to filter out outliers (motion vectors out of concern). The proposed adaptive robust estimation defines a continuous sigmoid weight function. It then adaptively tunes the sigmoid function to its hard-limit as the residual errors between the model and input data are decreased, so that we can effectively separate non-outliers (motion vectors of concern) from outliers with the finally tuned hard-limit of the weight function. The experimental results show that the suggested approach is very effective in filtering block motion vectors.
Keywords
adaptive weight function; minimization method; robust estimation;
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Times Cited By KSCI : 1  (Citation Analysis)
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