Video saliency detection using motion saliency filter

Lei Luo, Rongxin Jiang, Xiang Tian, Yao-wu Chen
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Abstract

In this paper, we propose a motion saliency filter to detect the salient regions in the video sequences. The motion vector field of each frame is first grouped into several elements with the aid of superpixel segmentation. Then, two measures are defined to rate the motion uniqueness and motion distribution of each element. The motion saliency of each element is derived as the fusion of the two measures. The final pixel-accurate saliency map is generated from a linear combination of the element motion saliency values. Moreover, the complete saliency computing process can be formulated with the N-D Gaussian filters which are with only linear computing complexity. Experimental results indicate that the proposed method could achieve better performance as compared to the state-of-the-art methods.
基于运动显著性滤波器的视频显著性检测
在本文中,我们提出了一种运动显著性滤波器来检测视频序列中的显著区域。首先利用超像素分割将每帧的运动向量场分成若干个元素;然后,定义了两个度量来评价每个元素的运动唯一性和运动分布。每个元素的运动显著性作为两个度量的融合而得到。最终的像素精确的显著性图是由元素运动显著性值的线性组合生成的。此外,完整的显著性计算过程可以用N-D高斯滤波器表示,其计算复杂度仅为线性。实验结果表明,与现有方法相比,该方法具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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