A compressed domain change detection algorithm for RTP streams in video surveillance applications

Marcus Laumer, P. Amon, A. Hutter, André Kaup
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引用次数: 6

Abstract

This paper presents a novel change detection algorithm for the compressed domain. Many video surveillance systems in practical use transmit their video data over a network by using the Real-time Transport Protocol (RTP). Therefore, the presented algorithm concentrates on analyzing RTP streams to detect major changes within contained video content. The paper focuses on a reliable preselection for further analysis modules by decreasing the number of events to be investigated. The algorithm is designed to work on scenes with mainly static background, like in indoor video surveillance streams. The extracted stream elements are RTP timestamps and RTP packet sizes. Both values are directly accessible by efficient byte-reading operations without any further decoding of the video content. Hence, the proposed approach is codec-independent, while at the same time its very low complexity enables the use in extensive video surveillance systems. About 40,000 frames per second of a single RTP stream can be processed on an Intel® CoreTM 2 Duo CPU at 2 GHz and 2 GB RAM, without decreasing the efficiency of the algorithm.
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视频监控中RTP流的压缩域变化检测算法
提出了一种新的压缩域变化检测算法。在实际应用中,许多视频监控系统使用实时传输协议(RTP)在网络上传输视频数据。因此,本文提出的算法侧重于分析RTP流,以检测包含视频内容的主要变化。通过减少待研究事件的数量,对进一步的分析模块进行了可靠的预选。该算法主要用于静态背景的场景,如室内视频监控流。提取的流元素是RTP时间戳和RTP数据包大小。这两个值都可以通过高效的字节读取操作直接访问,而无需对视频内容进行进一步解码。因此,所提出的方法是编解码器无关的,同时其非常低的复杂性使其能够在广泛的视频监控系统中使用。在2 GHz和2 GB RAM的Intel®CoreTM 2 Duo CPU上可以处理每秒约40,000帧的单个RTP流,而不会降低算法的效率。
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