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Genetic algorithm for inter-frame region object temporal correlation in binary partition tree

机译:二叉树中帧间区域对象时间相关的遗传算法

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摘要

Video contains rich information in the spatial and temporal domains. A single video shoot consists of a number of frames which are generally composed of similar objects which may have changed in position and size. The ability to recognize regions in the current frame is an important task in video analysis, but their subsequent recognition in the next frame receives little attention. This research utilizes a region based binary partition tree (BPT) as the content representation; object searching is conducted inside the binary tree and not in the original pixel domain. This work was conceived from the postulate: If an object exists inside a binary tree partition for a given video frame, can a corresponding branch be found in the BPT of the next frame? This is a difficult problem with a one to many and a many to one mapping and requires an innovative solution in the form of a Genetic algorithms (GA). GA's are ideally suited to this problem as the start and end conditions are known. This research proposes and achieves temporal correlation in region based BPTs using a genetic algorithm.
机译:视频包含时空域中的丰富信息。单个视频拍摄由许多帧组成,这些帧通常由位置和大小可能已更改的相似对象组成。识别当前帧中区域的能力是视频分析中的一项重要任务,但是在下一帧中对其后续的识别却很少受到关注。本研究利用基于区域的二进制分区树(BPT)作为内容表示。对象搜索是在二叉树内进行的,而不是在原始像素域内进行的。这项工作是从这样的假设中构思出来的:如果某个对象存在于给定视频帧的二叉树分区中,是否可以在下一帧的BPT中找到相应的分支?对于一对多和多对一映射,这是一个难题,需要采用遗传算法(GA)形式的创新解决方案。由于已知开始和结束条件,因此GA非常适合此问题。这项研究提出并使用遗传算法实现基于区域的BPT中的时间相关性。

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