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Dance Gesture Recognition Using Space Component And Effort Component Of Laban Movement Analysis

Dance is a collection of gestures that have many meanings. Dance is a culture that is owned by every country whose every movement has beauty or meaning contained in the dance movement. One obstacle in the development of dance is to recognize dance moves. In the process of recognizing dance movements...

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Main Authors: Joko Sutopo, Abd Ghani, Mohd Khanapi, Mohd Aboobaider, Burhanuddin, Zulhawati
Format: Article
Language:English
Published: International Journal of Scientific and Technology Research 2020
Online Access:http://eprints.utem.edu.my/id/eprint/25017/2/JOKOBURHANUDDINDANCEGESTURERECOGNITIONUSINGSPACECOMPONENT.PDF
http://eprints.utem.edu.my/id/eprint/25017/
http://www.ijstr.org/final-print/feb2020/Dance-Gesture-Recognition-Using-Space-Component-And-Effort-Component-Of-Laban-Movement-Analysis.pdf
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spelling my.utem.eprints.250172021-04-20T12:55:24Z http://eprints.utem.edu.my/id/eprint/25017/ Dance Gesture Recognition Using Space Component And Effort Component Of Laban Movement Analysis Joko Sutopo Abd Ghani, Mohd Khanapi Mohd Aboobaider, Burhanuddin Zulhawati Dance is a collection of gestures that have many meanings. Dance is a culture that is owned by every country whose every movement has beauty or meaning contained in the dance movement. One obstacle in the development of dance is to recognize dance moves. In the process of recognizing dance movements one of them is information technology by recording motion data using the Kinect sensor, where the results of the recording will produce a motion data format with the Biovision Hierarchy (BVH) file format. BVH motion data have position compositions (x, y, z). The results of the existing dance motion record will be extracted features using Laban Movement Analysis (LMA), where the LMA has four main components namely Body, Shape, Space, and Effort. After extracting the features, quantization, normalization, and classification will be performed. Using Hidden Markov Model (HMM). In this study using two LMA components, namely Space and Effort in extracting features in motion recognition patterns. From the results of the test and the resulting accuracy is approaching 99% for dance motion data. International Journal of Scientific and Technology Research 2020-02 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/25017/2/JOKOBURHANUDDINDANCEGESTURERECOGNITIONUSINGSPACECOMPONENT.PDF Joko Sutopo and Abd Ghani, Mohd Khanapi and Mohd Aboobaider, Burhanuddin and Zulhawati (2020) Dance Gesture Recognition Using Space Component And Effort Component Of Laban Movement Analysis. International Journal of Scientific and Technology Research, 9 (2). 3389 - 3394. ISSN 2277-8616 http://www.ijstr.org/final-print/feb2020/Dance-Gesture-Recognition-Using-Space-Component-And-Effort-Component-Of-Laban-Movement-Analysis.pdf
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description Dance is a collection of gestures that have many meanings. Dance is a culture that is owned by every country whose every movement has beauty or meaning contained in the dance movement. One obstacle in the development of dance is to recognize dance moves. In the process of recognizing dance movements one of them is information technology by recording motion data using the Kinect sensor, where the results of the recording will produce a motion data format with the Biovision Hierarchy (BVH) file format. BVH motion data have position compositions (x, y, z). The results of the existing dance motion record will be extracted features using Laban Movement Analysis (LMA), where the LMA has four main components namely Body, Shape, Space, and Effort. After extracting the features, quantization, normalization, and classification will be performed. Using Hidden Markov Model (HMM). In this study using two LMA components, namely Space and Effort in extracting features in motion recognition patterns. From the results of the test and the resulting accuracy is approaching 99% for dance motion data.
format Article
author Joko Sutopo
Abd Ghani, Mohd Khanapi
Mohd Aboobaider, Burhanuddin
Zulhawati
spellingShingle Joko Sutopo
Abd Ghani, Mohd Khanapi
Mohd Aboobaider, Burhanuddin
Zulhawati
Dance Gesture Recognition Using Space Component And Effort Component Of Laban Movement Analysis
author_facet Joko Sutopo
Abd Ghani, Mohd Khanapi
Mohd Aboobaider, Burhanuddin
Zulhawati
author_sort Joko Sutopo
title Dance Gesture Recognition Using Space Component And Effort Component Of Laban Movement Analysis
title_short Dance Gesture Recognition Using Space Component And Effort Component Of Laban Movement Analysis
title_full Dance Gesture Recognition Using Space Component And Effort Component Of Laban Movement Analysis
title_fullStr Dance Gesture Recognition Using Space Component And Effort Component Of Laban Movement Analysis
title_full_unstemmed Dance Gesture Recognition Using Space Component And Effort Component Of Laban Movement Analysis
title_sort dance gesture recognition using space component and effort component of laban movement analysis
publisher International Journal of Scientific and Technology Research
publishDate 2020
url http://eprints.utem.edu.my/id/eprint/25017/2/JOKOBURHANUDDINDANCEGESTURERECOGNITIONUSINGSPACECOMPONENT.PDF
http://eprints.utem.edu.my/id/eprint/25017/
http://www.ijstr.org/final-print/feb2020/Dance-Gesture-Recognition-Using-Space-Component-And-Effort-Component-Of-Laban-Movement-Analysis.pdf
_version_ 1698700619418697728
score 13.211869

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