The Study of Classifier Detection Time Based on OpenCV

摘要：

OpenCV can be used to detect picture modes with good effect. Here this paper will focus on detecting the palm. And the key step for palm detecting is to train a classifier. Therefore, the main content of the article is to train a classifier and test the classifier. Before training a classifier, it is necessary to get a lot of samples and them handle them. After training, there will be some experiments to study the factor which will affect on the detection time. Then, go to the source code of OpenCV, and find the relationship finally. At last, a good classifier is proposed.

关键词： classifier sample training size detection time false positive rate scale Factor

作者: Taotao Dai Yuchao Dou Hua Tian Ziqiang Huang

作者单位: Research Institute Electronic Science and Technology University of Electronic Science and Technology of China Chengdu, 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: 1044-1047

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）