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Joint motion estimation and segmentation based on the MDL principle

机译:基于MDL原理的联合运动估计和分割

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We consider the problem of joint motion segmentation and estimation. An algorithm based on region-merging and the Minimum Description Length (MDL) principle is presented here. The proposed technique is an unsupervised bottom-upmerging method which could be separated into two parts: initial segmentation and further segmentation. The error map of motion-compensated prediction error (MCPE) of each region is used to check the motion correlation of the contiguous regions and to obtain the motion vectors of the newly merged one. The MDL-based criteria are used to evaluate each possible fusion in further segmentation. The criteria are also used as a test for stopping the merging process. Experimental results demonstrate the efficiency of the proposed method.
机译:我们考虑关节运动分割和估计的问题。本文提出了一种基于区域合并和最小描述长度(MDL)原理的算法。所提出的技术是一种无监督的底部合并方法,可以将其分为两个部分:初始分割和进一步分割。每个区域的运动补偿预测误差(MCPE)的误差图用于检查连续区域的运动相关性,并获取新合并区域的运动矢量。基于MDL的标准用于评估进一步细分中的每种可能融合。该标准还用作停止合并过程的测试。实验结果证明了该方法的有效性。

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