Abstract
We propose a new stereo matching algorithm through energy-based regularization using color segmentation and visibility constraint. Plane parameters in the entire segments are modeled by robust least square algorithm, which is LMedS method. Then, plane parameter assignment is performed by the cost function penalized for occlusion, iteratively. Finally, disparity regularization which considers the smoothness between the segments and penalizes the occlusion through visibility constraint is performed. For occlusion and disparity estimation, we include the iterative optimization scheme in the energy-based regularization. Experimental results show that the proposed algorithm produces comparable performance to the state-of-the-arts especially in the object boundaries, un-textured regions.
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© 2006 Springer-Verlag Berlin Heidelberg
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Min, D., Yoon, S., Sohn, K. (2006). Segment-Based Stereo Matching Using Energy-Based Regularization. In: Gunsel, B., Jain, A.K., Tekalp, A.M., Sankur, B. (eds) Multimedia Content Representation, Classification and Security. MRCS 2006. Lecture Notes in Computer Science, vol 4105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11848035_100
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DOI: https://doi.org/10.1007/11848035_100
Publisher Name: Springer, Berlin, Heidelberg
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