Efficient Video Encoding for Automatic Video Analysis in Distributed Wireless Surveillance Systems
Efficient Video Encoding for Automatic Video Analysis in Distributed Wireless Surveillance Systems
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DOI：
10.1145/3226036
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发表时间：
2018-07
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影响因子：
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通讯作者：
Lingchao Kong;Rui Dai
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文献类型：
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作者：
Lingchao Kong;Rui Dai
在许多分布式无线监控应用中，压缩视频用于执行自动视频分析任务。对象检测的准确性，这是必不可少的各种视频分析任务，可以降低由于有损压缩引起的视频质量下降。本文介绍了一种视频编码框架，旨在提高无线监控应用中目标检测的准确性。所提出的视频编码框架是基于有损压缩对对象检测的影响的系统调查。已经发现，当前的标准化视频编码方案导致原始视频的稳定背景区域中的编码块的时域波动和动态前景区域中的编码块的空间纹理退化，这两者都降低了对象检测的准确性。引入绝对帧差和（SFD）和二维变换域纹理退化（TXD）两种测度，分别描述编码视频的时域波动和空间纹理退化。建议的编码框架的目的是抑制不必要的时间波动在稳定的背景区域，并保留空间纹理的动态前景区域的基础上的两个措施，它引入了新的模式决策策略帧内和帧间，以提高目标检测的准确性，同时保持可接受的率失真性能。实验结果表明，与传统的编码方案相比，该方案提高了目标检测的性能，并在PSNR和SSIM质量相当的情况下，降低了比特率和复杂度。
In many distributed wireless surveillance applications, compressed videos are used for performing automatic video analysis tasks. The accuracy of object detection, which is essential for various video analysis tasks, can be reduced due to video quality degradation caused by lossy compression. This article introduces a video encoding framework with the objective of boosting the accuracy of object detection for wireless surveillance applications. The proposed video encoding framework is based on systematic investigation of the effects of lossy compression on object detection. It has been found that current standardized video encoding schemes cause temporal domain fluctuation for encoded blocks in stable background areas and spatial texture degradation for encoded blocks in dynamic foreground areas of a raw video, both of which degrade the accuracy of object detection. Two measures, the sum-of-absolute frame difference (SFD) and the degradation of texture in 2D transform domain (TXD), are introduced to depict the temporal domain fluctuation and the spatial texture degradation in an encoded video, respectively. The proposed encoding framework is designed to suppress unnecessary temporal fluctuation in stable background areas and preserve spatial texture in dynamic foreground areas based on the two measures, and it introduces new mode decision strategies for both intra- and interframes to improve the accuracy of object detection while maintaining an acceptable rate distortion performance. Experimental results show that, compared with traditional encoding schemes, the proposed scheme improves the performance of object detection and results in lower bit rates and significantly reduced complexity with comparable quality in terms of PSNR and SSIM.