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Title: Live demonstration : a HMM-based real-time sign language recognition system with multiple depth sensors
Authors: Fok, KY
Cheng, CT 
Ganganath, N
Issue Date: 2015
Source: 2015 IEEE International Symposium on Circuits and Systems (ISCAS), Lisbon, Portugal, 24-27 May 2015, p. 1904
Abstract: Automatic sign language recognition plays an important role in communications for sign language users. Most existing sign language recognition systems use single sensor input. However, such systems may fail to recognize hand gestures correctly due to occluded regions of hand gestures. In this work, we propose a novel system for real-time recognition of the digits in American Sign Language (ASL) [1]. The proposed system [2] utilizes two Leap Motion sensors [3] to capture hand gestures from different angles. Sensory data are preprocessed using a multi-sensor data fusion approach and ASL digits are recognized in real-time from the fused data using Hidden Markov models (HMM) [4]. Experimental results of the proposed sign language recognition system demonstrate its improved performance over single sensor systems. With a low implementation cost and a high recognition accuracy, the proposed system can be widely adopted in many real world applications and bring conveniences to world-wide ASL users.
Keywords: Hidden Markov models
Image capture
Image fusion
Image motion analysis
Natural language processing
Sign language recognition
Publisher: Institute of Electrical and Electronics Engineers
ISSN: 0271-4302
DOI: 10.1109/ISCAS.2015.7169037
Rights: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
The following publication Fok, K. -., Cheng, C. -., & Ganganath, N. (2015). Live demonstration: A HMM-based real-time sign language recognition system with multiple depth sensors. Paper presented at the Proceedings - IEEE International Symposium on Circuits and Systems, ISCAS 2015, 1904 is available at 10.1109/ISCAS.2015.7169037
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