NDLI: A novel hand posture recognition system based on sparse representation using color and depth images

Content Provider	IEEE Xplore Digital Library
Author	Dan Xu Yen-Lun Chen Xinyu Wu Wei Feng Huihuan Qian Yangsheng Xu
Copyright Year	2013
Description	Author affiliation: Guangdong Provincial Key Lab. of Robot. & Intell. Syst., Shenzhen Inst. of Adv. Technol., Shenzhen, China (Dan Xu; Yen-Lun Chen; Xinyu Wu; Wei Feng) \|\| Dept. of Mech. & Autom. Eng., Chinese Univ. of Hong Kong, Hong Kong, China (Huihuan Qian; Yangsheng Xu)
Abstract	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.
Sponsorship	IEEE Ind. Electron. Soc.
Starting Page	3765
Ending Page	3770
File Size	7374626
Page Count	6
File Format	PDF
ISSN	21530858
DOI	10.1109/IROS.2013.6696894
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-03
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Color Image segmentation Image edge detection Joints Image color analysis Training
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Computer Science Applications Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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