计算机与现代化Issue(1)：74-77,4.DOI:10.3969/j.issn.1006-2475.2018.01.015
基于RGBD数据的静态手势识别
Static Hand Gesture Recognition Based on RGBD Data
文芳 1康彩琴 1陈立文 1丁汇 1徐琨 1王宁宁1
作者信息
- 1. 长安大学信息工程学院,陕西 西安 710064
- 折叠
摘要
Abstract
This paper proposes a hand gesture recognition algorithm based on RGBD data .Firstly, the gesture segmentation algo-rithm which combines depth data with color data is used to segment the hand gesture area more precisely .Secondly, circularity, convex hull points and convex defect points , 7Hu moment features of the segmented static gestures are extracted .Lastly, SVM are used to recognize different static hand gesture .The experimental results show that the proposed method can effectively identify the five kinds of static gestures , and has strong adaptability to the environment .关键词
手势识别/深度数据/手势分割/特征提取/SVMKey words
gesture recognition/depth data/gesture segmentation/feature extraction/SVM分类
信息技术与安全科学引用本文复制引用
文芳,康彩琴,陈立文,丁汇,徐琨,王宁宁..基于RGBD数据的静态手势识别[J].计算机与现代化,2018,(1):74-77,4.
