Presentation 2015-03-06
Gesture Recognition for Cooking Assistant System
Yuma HIJIOKA, Makoto MURAKAMI, Tadahiko KIMOTO,
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Abstract(in English) Our purpose is to recognize cooking gesture for showing cooking information on time. We make models for cooking gesture recognition. Our approach is extracting joint positions using Kinect, and structing model by HMMs. In this research, we use OpenNI/NiTE to extract features, and HTK to struct HMMs. When we select shoulders' and elbows' position as gesture features, structured models recognize gestures by 90.6%.
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Keyword(in English) Multimedia on cooking and eating activities / gesture recognition / depth image / machine learning / Hidden Markov Model
Paper # KBSE2014-60
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Conference Information
Committee KBSE
Conference Date 2015/2/26(1days)
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Registration To Knowledge-Based Software Engineering (KBSE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Gesture Recognition for Cooking Assistant System
Sub Title (in English)
Keyword(1) Multimedia on cooking and eating activities
Keyword(2) gesture recognition
Keyword(3) depth image
Keyword(4) machine learning
Keyword(5) Hidden Markov Model
1st Author's Name Yuma HIJIOKA
1st Author's Affiliation Guraduate School of Engineering, Toyo University()
2nd Author's Name Makoto MURAKAMI
2nd Author's Affiliation Faculty of Information Sciences and Arts, Toyo University
3rd Author's Name Tadahiko KIMOTO
3rd Author's Affiliation Faculty of Science and Engineering, Toyo University
Date 2015-03-06
Paper # KBSE2014-60
Volume (vol) vol.114
Number (no) 501
Page pp.pp.-
#Pages 5
Date of Issue