A framework for a video analysis tool for suspicious event detection
A framework for a video analysis tool for suspicious event detection
复制标题
用于可疑事件检测的视频分析工具框架
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
B. Thuraisingham
中科院分区：
文献类型：
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作者：
G. Lavee;L. Khan;B. Thuraisingham
本文提出了一个框架，以帮助视频分析人员在当今无处不在的监控视频世界中存在的大量视频数据中检测可疑活动。讨论了消除视频数据的低级机器可读特征与人类观察者看到的高级事件之间的语义差距的思想和技术。对事件分类和检测技术进行了评价，并提出了进一步完善该技术的实验。通过这些实验，讨论了最优的机器学习算法来学习本文提出的事件表示方案。
This paper proposes a framework to aid video analysts in detecting suspicious activity within the tremendous amounts of video data that exists in today’s world of omnipresent surveillance video. Ideas and techniques for closing the semantic gap between low-level machine readable features of video data and high-level events seen by a human observer are discussed. An evaluation of the event classification and detection technique is presented and a future experiment to refine this technique is proposed. These experiments are used as a lead to a discussion on the most optimal machine learning algorithm to learn the event representation scheme proposed in this paper.