NDLI: Design of body gesture recognition system for regularity and repeatability gestures

Content Provider	IEEE Xplore Digital Library
Author	Jae-Hwan Choi Deok-Hyun Ko Hyung Kim Soon-Geul Lee
Copyright Year	2014
Description	Author affiliation: Solution Provide Team, Uinfraway, Suwon, South Korea (Deok-Hyun Ko) \|\| Dept. of Mech. Eng., Kyung-Hee Univ., Yongin, South Korea (Jae-Hwan Choi; Hyung Kim; Soon-Geul Lee)
Abstract	People often use non-linguistic communication methods such as physical gestures, which compose over 70% of our overall interaction with others. These physical gestures have regularity and repeatability as their common traits. This study is mainly discussing gesture recognition system for regular and repeated gestures. Torso PCA frame method is applied to angle transformation for such gesture recognition. In addition, a feature set is defined through extracting the patterns using envelope detection method and is applied to multi-layer perceptron for gesture recognition. For our experiment, skeletal structure was collected using Kinect, and 8 gestures were selected that people regularly use in real life. The recognition system was confirmed based on variety of people as our sample and the average accuracy was 89%.
Starting Page	449
Ending Page	453
File Size	1100040
Page Count	5
File Format	PDF
ISSN	20937121
e-ISBN	9788993215076
DOI	10.1109/ICCAS.2014.6988039
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-22
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Control, Robotics and Systems (ICROS)
Subject Keyword	Kinect Image recognition body gesture recognition human robot Interaction(HRI) Heating Hidden Markov models Feature extraction multi-layer perceptron(MLP) Pattern recognition Noise measurement Elbow
Content Type	Text
Resource Type	Article

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