Video saliency-detection using custom spatiotemporal fusion method

Vinay C. Warad, Ruksar Fatima
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Abstract

There have been several researches done in the field of image saliency but not as much as in video saliency. In order to increase precision and accuracy during compression, reduce coding complexity and time consumption along with memory allocation problems with our proposed solution. It is a modified high-definition video compression (HEVC) pixel based consistent spatiotemporal diffusion with temporal uniformity. It involves taking apart the video into groups of frames, computing colour saliency, integrate temporal fusion, pixel saliency fusion is conducted and then colour information guides the diffusion process for the spatiotemporal mapping with the help of permutation matrix. The proposed solution is tested on a publicly available extensive dataset with five global saliency valuation metrics and is compared with several other state-of-the-art saliency detection methods. The results display and overall best performance amongst all other candidates.
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基于自定义时空融合方法的视频显著性检测
在图像显著性领域已经有了一些研究,但在视频显著性方面的研究还不够多。为了提高压缩过程中的精度和准确性,我们提出的解决方案可以减少编码复杂性和时间消耗以及内存分配问题。它是一种基于时间均匀性的一致时空扩散的改进的高清视频压缩(HEVC)像素。它包括将视频分解成帧组,计算颜色显著性,积分时间融合,进行像素显著性融合,然后借助排列矩阵引导颜色信息的扩散过程进行时空映射。提出的解决方案在具有五个全球显著性评估指标的公开广泛数据集上进行了测试,并与其他几种最先进的显著性检测方法进行了比较。在所有候选人中,结果显示和整体表现最佳。
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