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Proceedings Paper

Non-intrusive gesture recognition system combining with face detection based on Hidden Markov Model
Author(s): Jing Jin; Yuanqing Wang; Liujing Xu; Liqun Cao; Lei Han; Biye Zhou; Minggao Li
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Paper Abstract

A non-intrusive gesture recognition human-machine interaction system is proposed in this paper. In order to solve the hand positioning problem which is a difficulty in current algorithms, face detection is used for the pre-processing to narrow the search area and find user’s hand quickly and accurately. Hidden Markov Model (HMM) is used for gesture recognition. A certain number of basic gesture units are trained as HMM models. At the same time, an improved 8-direction feature vector is proposed and used to quantify characteristics in order to improve the detection accuracy. The proposed system can be applied in interaction equipments without special training for users, such as household interactive television

Paper Details

Date Published: 4 November 2014
PDF: 9 pages
Proc. SPIE 9273, Optoelectronic Imaging and Multimedia Technology III, 92731F (4 November 2014); doi: 10.1117/12.2072579
Show Author Affiliations
Jing Jin, Nanjing Univ. (China)
Yuanqing Wang, Nanjing Univ. (China)
Liujing Xu, Nanjing Univ. (China)
Liqun Cao, Navy General Hospital (China)
Lei Han, Navy General Hospital (China)
Biye Zhou, Navy General Hospital (China)
Minggao Li, Navy General Hospital (China)


Published in SPIE Proceedings Vol. 9273:
Optoelectronic Imaging and Multimedia Technology III
Qionghai Dai; Tsutomu Shimura, Editor(s)

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