Joint depth-motion dense estimation for multiview video coding

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• 作者：Ismaë ; l Daribo ; Wided Miled ; Bé ; atrice Pesquet-Popescu
• 关键词：Multiview ; Video coding ; Depth ; Joint motion-depth estimation ; Total variation ; Convex optimization ; H.264/MPEG-4 AVC ; MVC
• 刊名：Journal of Visual Communication and Image Representation
• 出版年：2010
• 出版时间：July-August 2010
• 年：2010
• 卷：21
• 期：5-6
• 页码：487-497
• 全文大小：754 K

文摘

The multiview video coding (MVC) extension of H.264/MPEG-4 AVC [1] is one of the most promising visual encoders for three-dimensional television and free viewpoint video applications. In this paper, we propose a joint dense motion/disparity estimation algorithm, designed to replace the classical temporal/inter-view unit within MVC, which uses a block-based motion/disparity estimation. The motion vector fields and the disparity vector fields are therefore simultaneously derived using the stereo-motion consistency constraint in a set theoretic convex optimization framework. The obtained displacement vector fields are then jointly segmented by minimizing a rate-distortion cost function, in line with the multiple reference frame strategy used in H.264/MPEG-4 AVC. Experimental results demonstrate the benefits of the proposed method compared to the separated dense estimation scheme or the block-based estimation technique.