Sparse Representation for Kinect Based Hand Gesture Recognition System
Zeke Xu, Zhenhao Huang, Zhuoxiong Zhao, Zhiyuan Li, Pengsen Huang
Available Online August 2013.
- https://doi.org/10.2991/icaicte.2013.125How to use a DOI?
- human-computer interaction, hand gesture recognition system, sparse representation, Kinect, auto-encoder neu-ral network computation
- Hand gesture recognition that has proven a significant factor to directly influence the nonverbal communication between human and computer is becoming a chal-lenging topic in the field of machine vi-sion. This paper aims to propose a novel hand gesture recognition system which applies sparse representation to the Kinect to improve the efficiency of Kinect-based human-computer interac-tion. Auto-encoder neural network com-putation is also utilized to achieve better result. The sparse auto-encoder neural network is versatile and robust in com-plex features learning and computational efficient. Finally, results indicate that our algorithm greatly facilitates the gesture recognition rate up to 95%.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Zeke Xu AU - Zhenhao Huang AU - Zhuoxiong Zhao AU - Zhiyuan Li AU - Pengsen Huang PY - 2013/08 DA - 2013/08 TI - Sparse Representation for Kinect Based Hand Gesture Recognition System BT - 2013 International Conference on Advanced ICT and Education (ICAICTE-13) PB - Atlantis Press SP - 610 EP - 616 SN - 1951-6851 UR - https://doi.org/10.2991/icaicte.2013.125 DO - https://doi.org/10.2991/icaicte.2013.125 ID - Xu2013/08 ER -