计算机技术与发展2016，Vol.26Issue(8)：200-204,5.DOI:10.3969/j.issn.1673-629X.2016.08.043
基于骨骼和深度信息的手势识别的研究与应用
Research and Application of Gesture Recognition Based on Information of Body Skeleton and Depth
摘要
Abstract
It explores the technology of gesture recognition based on Kinect in this paper,and designs and implements a small gesture in-teractive system with perfect function and excellent performance. At first,the Skeleton Information and Depth Information from Kinect is used to track and extract hand from the background. The result doesn’ t be affected by the background,light,and experimenter’ s skin col-or and costume. Then,according to the distribution of noise from preliminary acquisition in the binary images,a method of filtering the small scale connected component pixels is put forward to denoise. At last,Hu’ s moments of hand binary images and hand contour binary images are used as features to train the Support Vector Machine ( SVM) classifiers respectively. The experimental results show that com-pared with Hu’ s moments of hand binary images,the Hu’ s moments of the hand contour binary images have obvious advantages.关键词
静态手势识别/手势交互系统/Hu矩/支持向量机Key words
static gesture recognition/gesture interactive system/Hu’s moment/support vector machine分类
信息技术与安全科学引用本文复制引用
吴彩芳,谢钧,俞璐..基于骨骼和深度信息的手势识别的研究与应用[J].计算机技术与发展,2016,26(8):200-204,5.基金项目
国家“863”高技术发展计划项目(2012aa01a509,2012aa01a510) （2012aa01a509,2012aa01a510）
