QQ客服 官方微博 反馈留言

	A novel hand posture recognition system based on sparse representation using color and depth images
	Xu Dan; Chen Yen-Lun; Wu Xinyu; Feng Wei; Qian Huihuan; Xu Yangsheng
	2013
会议名称	2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013
会议地点	Tokyo, Japan
英文摘要	Hand posture is a natural and effective human robot interaction way. In this paper, an user-independent hand posture recognition system using depth and color images captured from an RGB-D camera is presented. To recognize hand posture against complicated background conditions, we propose a novel method for automatic and accurate hand posture segmentation which detects the hand with Chamfer matching, tracks the hand with Kalman filter and segments the hand with region growing algorithm only in the depth space. A new hand posture descriptor invariant to scale, shift and in-plane rotation is constructed with the combination of local contour Fourier descriptor and global Bag-of-Features (BoF) descriptor based on Scale Invariance Feature Transform (SIFT). The sparse representation-based classification (SRC) is applied to perform the hand posture recognition task in the system. Experiments with a self-built large scale hand posture database collected online show the robustness and effectiveness of the proposed system.
收录类别	EI
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/4593]
专题	深圳先进技术研究院_集成所
作者单位	2013
推荐引用方式 GB/T 7714	Xu Dan,Chen Yen-Lun,Wu Xinyu,et al. A novel hand posture recognition system based on sparse representation using color and depth images[C]. 见:2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013. Tokyo, Japan.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。