Feature Extraction for Human Motion Indexing of Acted Dance Performances

Andreas Aristidou, Yiorgos Chrysanthou

2014

Abstract

There has been an increasing use of pre-recorded motion capture data for animating virtual characters and synthesising different actions; it is although a necessity to establish a resultful method for indexing, classifying and retrieving motion. In this paper, we propose a method that can automatically extract motion qualities from dance performances, in terms of Laban Movement Analysis (LMA), for motion analysis and indexing purposes. The main objectives of this study is to analyse the motion information of different dance performances, using the LMA components, and extract those features that are indicative of certain emotions or actions. LMA encodes motions using four components, Body, Effort, Shape and Space, which represent a wide array of structural, geometric, and dynamic features of human motion. A deeper analysis of how these features change on different movements is presented, investigating the correlations between the performers' acting emotional state and its characteristics, thus indicating the importance and the effect of each feature for the classification of the motion. Understanding the quality of the movement helps to apprehend the intentions of the performer, providing a representative search space for indexing motions.

Paper Citation

in Harvard Style

Aristidou A. and Chrysanthou Y. (2014). Feature Extraction for Human Motion Indexing of Acted Dance Performances . In Proceedings of the 9th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2014) ISBN 978-989-758-002-4, pages 277-287. DOI: 10.5220/0004662502770287

in Bibtex Style

@conference{grapp14,
author={Andreas Aristidou and Yiorgos Chrysanthou},
title={Feature Extraction for Human Motion Indexing of Acted Dance Performances},
booktitle={Proceedings of the 9th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2014)},
year={2014},
pages={277-287},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004662502770287},
isbn={978-989-758-002-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2014)
TI - Feature Extraction for Human Motion Indexing of Acted Dance Performances
SN - 978-989-758-002-4
AU - Aristidou A.
AU - Chrysanthou Y.
PY - 2014
SP - 277
EP - 287
DO - 10.5220/0004662502770287