A taxonomic overview and pilot study for evaluation of Augmented Reality based posture matching technique using Technology Acceptance Model

Motor skill training, posture matching and Augmented Reality (AR) based learning technology are considered to be the cornerstones of dance learning paradigm. In this paper, an AR based posture matching technique is presented based upon skeletal mapping and movement matching where each posture is mod...

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Bibliographic Details
Published in:Procedia computer science 2019, Vol.163, p.345-351
Main Authors: Iqbal, Javid, Sidhu, Manjit Singh
Format: Article
Language:English
Subjects:
Augmented Reality
Dance learning
Kinect
pose matching
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Summary:Motor skill training, posture matching and Augmented Reality (AR) based learning technology are considered to be the cornerstones of dance learning paradigm. In this paper, an AR based posture matching technique is presented based upon skeletal mapping and movement matching where each posture is modelled by a sequence of pivotal movements and continuous data frames. An extension of the previously published work by the authors, this paper aims to provide a taxonomic overview of dance learning/ training technologies with respect to existing learning theories. Furthermore, the proposed system is evaluated using the Technology Acceptance Model (TAM) and a pilot study is carried out to assess the acceptability of the system. The results of the pilot study are also utilized for identifying flaws and to calculate the sample size for further evaluation using a larger group of subjects. This research also aims at providing a taxonomical knowledge and categorization of the proposed Augmented Reality Dance Training System (ARDTS) in the state-of-art hierarchical structure of learning theories.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2019.12.117