陈颖鸣, 陈树越, 张显亭. 智能视频监控中异常行为识别研究[J]. 微电子学与计算机, 2010, 27(11): 102-105.
引用本文: 陈颖鸣, 陈树越, 张显亭. 智能视频监控中异常行为识别研究[J]. 微电子学与计算机, 2010, 27(11): 102-105.
CHEN Ying-ming, CHEN Shu-yue, ZHANG Xian-ting. Research on Abnormal Behavior Recognition in Intelligent Surveillance[J]. Microelectronics & Computer, 2010, 27(11): 102-105.
Citation: CHEN Ying-ming, CHEN Shu-yue, ZHANG Xian-ting. Research on Abnormal Behavior Recognition in Intelligent Surveillance[J]. Microelectronics & Computer, 2010, 27(11): 102-105.

智能视频监控中异常行为识别研究

Research on Abnormal Behavior Recognition in Intelligent Surveillance

  • 摘要: 通过对HSV空间阴影检测与RGB空间阴影检测进行比较,分析了两种方法对消除阴影的效果,得出采用RGB空间阴影检测方法消除阴影对运动目标的识别更为准确.通过给出人的异常行为判别准则来识别运动目标是否属于消失、攀爬、跌倒等情况,实验结果表明该识别方法简单、快速、准确,取得了较好的识别效果.

     

    Abstract: This paper first compares HSV space for shadow detection and RGB space for shadow detection and analyze the effect on eliminating the shadow. The author concludes that RGB space for shadow detection is more suitable for detection of moving targets. What's more, in this paper, a couple of criterions are defined to analyze whether people disappear, climb, or fall. Experiments demonstrate that the approach which is proposed on abnormal behavior recognition is easy, fast and effective and aehieves good recognition effect.

     

/

返回文章
返回