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Video sequence segmentation using genetic algorithms

机译:使用遗传算法的视频序列分割

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This paper proposes a new video sequence segmentation method based on the genetic algorithm (GA) that can improve computational efficiency. The computation is distributed into chromosomes that evolve using distributed genetic algorithms(DGAs). Each chromosome consists of a label and feature vector. The label is used as the region number for the pixel where the chromosome is located. Based on the temporal correlation between two consecutive frames in a video sequence, the segmentation of a frame is successively obtained using the segmentation result of the previous frame. In addition to eliminating redundant computation, only unstable chromosomes corresponding to moving object parts are evolved. Experimental results confirm the effectiveness of the proposed method.
机译:提出了一种基于遗传算法的视频序列分割新方法,可以提高计算效率。计算被分配到使用分布式遗传算法(DGA)进化的染色体中。每个染色体均由标记和特征向量组成。该标签用作染色体所在像素的区域编号。基于视频序列中两个连续帧之间的时间相关性,使用前一帧的分割结果连续获取帧的分割。除了消除冗余计算之外,仅进化出对应于运动对象部分的不稳定染色体。实验结果证实了该方法的有效性。

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