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Highlight moving object detection based on spatiotemporal saliency in dynamic background

机译:动态背景下基于时空显着性的高亮运动目标检测

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Changing area extraction from the sequential images is the main role of motion detect, the detection result will be seriously affected by the dynamic background, so that the efficient motion detection becomes a difficult task. Inspired by the saliency detection, this paper presents a new method for moving object detection, combined with the bottom-up and top-down visual computing model to obtain spatiotemporal saliency. The proposed method detected the spatial saliency map, and adds a time dimension on its basis to obtain the temporal saliency map by using the idea of a three-frame difference to detect the salient moving object in the video. The proposed method is simple and effective to detect salient motion region. Experiment results shown that the detected moving object was salient in dynamic background, and good to overcome the difficulties in special circumstances in which camera shakes ceaselessly. This method has widely applicable and better robustness.
机译:从顺序图像中提取区域变化是运动检测的主要作用,动态背景会严重影响检测结果,因此有效的运动检测成为一项艰巨的任务。受显着性检测的启发,本文提出了一种新的运动目标检测方法,结合自下而上和自上而下的视觉计算模型来获得时空显着性。所提出的方法检测了空间显着图,并在其基础上增加了一个时间维度,以利用三帧差的思想来检测视频中的显着运动物体,从而获得了时间显着图。该方法简单有效。实验结果表明,所检测到的运动物体在动态背景下是显着的,很好地克服了相机不断抖动的特殊情况下的困难。该方法具有广泛的适用性和较好的鲁棒性。

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