Liu Pengyu, Jia Kebin
School of Electronic Information & Control Engineering, Beijing University of Technology, Beijing 100124, China.
ScientificWorldJournal. 2013 Dec 23;2013:293681. doi: 10.1155/2013/293681. eCollection 2013.
A low-complexity saliency detection algorithm for perceptual video coding is proposed; low-level encoding information is adopted as the characteristics of visual perception analysis. Firstly, this algorithm employs motion vector (MV) to extract temporal saliency region through fast MV noise filtering and translational MV checking procedure. Secondly, spatial saliency region is detected based on optimal prediction mode distributions in I-frame and P-frame. Then, it combines the spatiotemporal saliency detection results to define the video region of interest (VROI). The simulation results validate that the proposed algorithm can avoid a large amount of computation work in the visual perception characteristics analysis processing compared with other existing algorithms; it also has better performance in saliency detection for videos and can realize fast saliency detection. It can be used as a part of the video standard codec at medium-to-low bit-rates or combined with other algorithms in fast video coding.
提出了一种用于感知视频编码的低复杂度显著性检测算法；采用低级编码信息作为视觉感知分析的特征。首先，该算法利用运动矢量（MV）通过快速MV噪声滤波和平移MV检查过程来提取时间显著性区域。其次，基于I帧和P帧中的最佳预测模式分布来检测空间显著性区域。然后，它结合时空显著性检测结果来定义视频感兴趣区域（VROI）。仿真结果验证了所提算法与其他现有算法相比，在视觉感知特征分析处理中可以避免大量的计算工作；它在视频显著性检测方面也具有更好的性能，并且能够实现快速显著性检测。它可以用作中低比特率视频标准编解码器的一部分，或者在快速视频编码中与其他算法相结合。
