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. |
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