A STATISTICAL PARAMETER LEARNING METHOD FOR CAST SHADOW MODEL

摘要：

In special video surveillance environment, the intensity variance of cast shadow of independent moving objects has its own special statistical model. This paper proposes statistical parameter estimation method for cast shadow of moving objects, based on statistical correlation in the situation of stationary cameras. In view of pixels belonging to moving shadow show stably statistical characteristics, while that belongs to different moving targets have weak correlation among them, we obtain a stably statistical distribution of shadows by a correlation calculation of histograms from many detected moving regions. It could give a credible partition between moving targets and moving shadows. Simple shadow detection method based on our statistical model can be used to detect cast shadow of moving objects. Experimental results demonstrate that our technique can detect moving cast shadows robustly in an efficient and simple way.

关键词： Video surveillance shadow correlation histogram

作者: HONG-HUA LIN JI-HONG PEI DE-JIAN LIU XUAN YANG

作者单位: College of Information Engineering, Shenzhen University, Shenzhen, 518060, China Intelligent Information Processing Laboratory of Shenzhen University, Shenzhen, 518060, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 2234-2239

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）