Authors:
Andreas Aristidou
and
Yiorgos Chrysanthou
Affiliation:
University of Cyprus, Cyprus
Keyword(s):
Motion Capture, Laban Movement Analysis, Motion Indexing, Emotions.
Related
Ontology
Subjects/Areas/Topics:
Animation and Simulation
;
Animation from Motion Capture
;
Behavioural Animation
;
Computer Vision, Visualization and Computer Graphics
;
Emotion and Personality
;
Evaluation of Human Performance and Usability in Virtual Environments
;
Interactive Environments
;
Motion Synthesis
;
Social Agents in Computer Graphics
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 characterist
ics, 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.
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