Hands Detection Based on Statistical Learning

摘要：

This paper proposes a hand detection method based on statistical learning training way. Using Microsofts Kinect sensor, to get the depth information. Through the analysis of the characetristics of hands, put out a kind of new features for statistical learning which approximate with Harr-like feature. The new feature is good at describing complex hand shape degeneration. With the help of Adaboost statistical learning, gets the training model. Experiment results demonstrate that using the new features with Adaboost algorithm can achieve more rapid and robust hands detection system.

关键词： Kinect Harr-like Adaboost hands detection training

作者: Hui Li Lei Yang Xiaoyu Wu Jun Zhai

作者单位: Digital Media Department,Communication University of China Beijing, China Information Construction Office Tianjin University of Finance & Economic Tianjin, China

会议类型: 国际会议

会议名称: 2012 Fifth International Symposium on Computational Intelligence and Design 第五届计算智能与设计国际会议 ISCID 2012

会议地点: 杭州

会议语种:英文

页码: 805-808

在线出版日期: 2012-10-28（万方平台首次上网日期，不代表论文的发表时间）