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Salient Object Detection via Video Spatio-Temporal Difference and Coherence

机译:通过视频时空差异和相干性检测显着物体

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Recent advances in salient object detection in images have achieved obvious performance in various multimedia applications, but efficient salient object detection in videos is still a challenging problem. In this paper, we propose a novel salient object detection method based on spatio-temporal difference and coherence of video content. Firstly, we initialize the saliency map for each keyframe based on spatial difference on color cue and temporal difference on motion cue. Then, we propagate the saliency among the regions intra and inter frames according to spatio-temporal coherence, in order to generate the saliency maps for other frames and refine the saliency maps of all the frames. By combining spatio-temporal difference and coherence, we can efficiently detect the salient objects in videos. The proposed method is evaluated on the public UVSD data set, and the experimental results show that our method outperforms the state-of-the-art methods by considering both effectiveness and efficiency.
机译:图像中的显着目标检测的最新进展在各种多媒体应用中已取得了明显的性能,但是视频中有效的显着目标检测仍然是一个充满挑战的问题。在本文中,我们提出了一种基于时空差异和视频内容相干性的显着目标检测方法。首先,我们根据颜色提示的空间差异和运动提示的时间差异初始化每个关键帧的显着性图。然后,我们根据时空相关性在区域内和帧间区域之间传播显着性,以生成其他帧的显着性图,并细化所有帧的显着性图。通过结合时空差异和连贯性,我们可以有效地检测视频中的显着对象。在公开的UVSD数据集上对提出的方法进行了评估,实验结果表明,通过兼顾有效性和效率,我们的方法优于最新方法。

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