视频的视觉显著性估计

Matthew Oakes, G. Abhayaratne
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引用次数: 6

摘要

图像或视频中最引人注目的区域可以通过利用人类视觉系统的特性来捕获。本文提出了一种新的视频序列视觉显著性信息建模方法。该方法结合小波分解和人类视觉系统建模来捕获时空显著性信息。提出了一种独特的方法来捕获和结合突出运动数据与空间强度和方向对比的序列。与现有方法相比,该方法具有更好的性能。该快速算法实现简单,可用于许多基于小波的应用,如水印、压缩和融合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Visual saliency estimation for video
The most eye catching regions within an image or video can be captured by exploiting characteristics within the human visual system. In this paper we propose a novel method for modeling the visual saliency information in a video sequence. The proposed method incorporates wavelet decomposition and the modeling of the human visual system to capture spatiotemporal saliency information. A unique approach to capture and combine salient motion data with spatial intensity and orientation contrasts in the sequence, is presented. The proposed method shows a superior performance compared to the state-of-the-art existing methods. The fast algorithm can be simply implemented and is useful for many wavelet based applications such as watermarking, compression and fusion.
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