Video Data Mining based on K-means Algorithm for Surveillance Video

摘要：

In this paper, we propose a new data mining algorithm, which is used in surveillance video of stationary places. The algorithm combines Background Subtraction with Symmetrical Differencing in order to extract moving targets. According to the amount of motions occurring in video frames, we divide the video into different segments. Video segments are clustered via the improved K-Means algorithm. Then we find the abnormal events, congestions and similar situation retrieval effectively in this way. To a certain extent, intelligent surveillance is implemented well.

关键词： K-means surveillance video mining video mining

作者: Jinghua Wang Guoyan Zhang

作者单位: Computer Science and Technology Department, Hua Zhong Normal University, Wu Han, Hu Bei, China

会议类型: 国际会议

会议名称: 2011 International Conference on Image Analysis and Signal Processing(2011第三届图像分析与信号处理国际会议 IASP 2011)

会议地点: 武汉

会议语种:英文

页码: 623-626

在线出版日期: 2011-10-21（万方平台首次上网日期，不代表论文的发表时间）