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An automatic segmentation algorithm for moving objects in video sequences under multi-constraints

机译:多约束下视频序列中运动对象的自动分割算法

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A new algorithm under multi-constraints for automatic segmentation of video moving objects is proposed. First, the temporal segmentation separates the initial areas including moving objects accurately from the background by continuous frame difference. Then, the spatial segmentation segments the initial areas into spatially consistent regions by the watershed algorithm based on a color gradient. Finally, regions are classified as foreground/background by maximizing the a posterior probability (MAP) of the MRF with spatial, temporal and adjacent constraints. Experimental results demonstrate that the algorithm is not sensitive to objects' irregular movement and illumination, and it can extract moving video objects accurately.
机译:提出了一种在多约束下视频运动目标自动分割的新算法。首先,时间分割通过连续的帧差将包括运动对象的初始区域与背景准确地分开。然后,空间分割通过基于颜色梯度的分水岭算法将初始区域分割为空间上一致的区域。最后,通过最大化具有空间,时间和邻近约束的MRF的后验概率(MAP),将区域分类为前景/背景。实验结果表明,该算法对物体的不规则运动和光照不敏感,可以准确地提取运动视频对象。

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