Paper Info
Title
Folk Dance Evaluation Using Laban Movement Analysis
Abstract
Motion capture (mocap) technology is an efficient method for digitizing art performances, and is becoming increasingly popular in the preservation and dissemination of dance performances. Although technically the captured data can be of very high quality, dancing allows stylistic variations and improvisations that cannot be easily identified. The majority of motion analysis algorithms are based on ad-hoc quantitative metrics, thus do not usually provide insights on style qualities of a performance. In this work, we present a framework based on the principles of Laban Movement Analysis (LMA) that aims to identify style qualities in dance motions. The proposed algorithm uses a feature space that aims to capture the four LMA components (Body, Effort, Shape, Space), and can be subsequently used for motion comparison and evaluation. We have designed and implemented a prototype virtual reality simulator for teaching folk dances in which users can preview dance segments performed by a 3D avatar and repeat them. The user’s movements are captured and compared to the folk dance template motions; then, intuitive feedback is provided to the user based on the LMA components. The results demonstrate the effectiveness of our system, opening new horizons for automatic motion and dance evaluation processes.
Year
DOI
Venue
2015
10.1145/2755566
ACM Journal on Computing and Cultural Heritage
Keywords
Field
DocType
Folk dances,Laban Movement Analysis,motion capture,motion comparison,motion evaluation
Motion capture,Feature vector,Pace,Dance,Folk dance,Computer science,Motion analysis,Multimedia,Avatar,Laban Movement Analysis
Journal
Volume
Issue
ISSN
8
4
1556-4673
Citations 
PageRank 
References 
9
0.48
27
Authors
5
Name
Order
Citations
PageRank
Andreas Aristidou122115.34
Efstathios Stavrakis2905.93
Panayiotis Charalambous3302.93
Yiorgos Chrysanthou483775.96
Stephania Loizidou Himona5171.38