Real-time Hand Posture Analysis based on Neural Network

摘要：

In this paper, a modified Neural Gas algorithm is proposed and used to approximate hand topology. As original Neural Gas algorithm is intractable for real-time applications, some optimization such as unnecessary adaption removal and simple learning rate function are introduced to make it applicable for real-time applications. With segmented hand area, the topology representation can be obtained based on neural network. The topology based representation of hand shape will further facilitate both fingertip localization and posture recognition. Experiments show the accuracy and the speed of our method can satisfy realtime requirements of interaction applications, even on mobile devices.

关键词： Neural Gas hand posture recognition,shape represention,camera-projector system

作者: Yang Shi Xiang Chen Kongqiao Wang Yikai Fang Lei Xu

作者单位: Department of Electrical Science and Technology University of Science and Technology of China Hefei, Nokia Research Center, Beijing Beijing, China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 893-896

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）