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AR oriented pose matching mechanism from motion capture data

Pose matching and skeletal mapping method are an integral part of Augmented Reality (AR) based learning technology. In this paper a mechanism for pose matching is presented based on extraction of skeletal data from the dance trainer's physical movements in the form of color defined images snapp...

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Main Authors: Iqbal J., Sidhu M.S., Ariff M.B.M.
Other Authors: 57200394167
Format: Article
Published: Science Publishing Corporation Inc 2023
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id my.uniten.dspace-24062
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spelling my.uniten.dspace-240622023-05-29T14:54:58Z AR oriented pose matching mechanism from motion capture data Iqbal J. Sidhu M.S. Ariff M.B.M. 57200394167 56259597000 57205240987 Pose matching and skeletal mapping method are an integral part of Augmented Reality (AR) based learning technology. In this paper a mechanism for pose matching is presented based on extraction of skeletal data from the dance trainer's physical movements in the form of color defined images snapped by Kinect, where each pose is modelled by a sequence of key movements and continues data frames. In order to extract the exact matched pose, the frame sequence is divided into pose feature frame and skeletal data frame by the use of pose matching dance training movement recognition algorithm (PMDTMR). This proposed algorithm is compared with other published methods in terms of frame level accuracy and learning time of dance session. The experimental results show that the proposed algorithm outperforms the state of art techniques for successful identification and recognition of matched pose between the dance trainer and the expert of the pre-recorded video through the Kinect sensor. � 2018 Authors. Final 2023-05-29T06:54:57Z 2023-05-29T06:54:57Z 2018 Article 10.14419/ijet.v7i4.35.22749 2-s2.0-85059233144 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059233144&doi=10.14419%2fijet.v7i4.35.22749&partnerID=40&md5=bc329dcc8980ed7f00d9eefa44d0ea9c https://irepository.uniten.edu.my/handle/123456789/24062 7 4 294 298 All Open Access, Green Science Publishing Corporation Inc Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Pose matching and skeletal mapping method are an integral part of Augmented Reality (AR) based learning technology. In this paper a mechanism for pose matching is presented based on extraction of skeletal data from the dance trainer's physical movements in the form of color defined images snapped by Kinect, where each pose is modelled by a sequence of key movements and continues data frames. In order to extract the exact matched pose, the frame sequence is divided into pose feature frame and skeletal data frame by the use of pose matching dance training movement recognition algorithm (PMDTMR). This proposed algorithm is compared with other published methods in terms of frame level accuracy and learning time of dance session. The experimental results show that the proposed algorithm outperforms the state of art techniques for successful identification and recognition of matched pose between the dance trainer and the expert of the pre-recorded video through the Kinect sensor. � 2018 Authors.
author2 57200394167
author_facet 57200394167
Iqbal J.
Sidhu M.S.
Ariff M.B.M.
format Article
author Iqbal J.
Sidhu M.S.
Ariff M.B.M.
spellingShingle Iqbal J.
Sidhu M.S.
Ariff M.B.M.
AR oriented pose matching mechanism from motion capture data
author_sort Iqbal J.
title AR oriented pose matching mechanism from motion capture data
title_short AR oriented pose matching mechanism from motion capture data
title_full AR oriented pose matching mechanism from motion capture data
title_fullStr AR oriented pose matching mechanism from motion capture data
title_full_unstemmed AR oriented pose matching mechanism from motion capture data
title_sort ar oriented pose matching mechanism from motion capture data
publisher Science Publishing Corporation Inc
publishDate 2023
_version_ 1806427696666771456
score 13.223943

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