A motion capture library for the study of identity, gender, and emotion perception from biological motion

Ma, YingLiang ORCID: https://orcid.org/0000-0001-5770-5843, Paterson, Helena M. and Pollick, Frank E. (2006) A motion capture library for the study of identity, gender, and emotion perception from biological motion. Behavior Research Methods, 38. 134–141. ISSN 1554-351X

Full text not available from this repository. (Request a copy)

Abstract

We present the methods that were used in capturing a library of human movements for use in computeranimated displays of human movement. The library is an attempt to systematically tap into and represent the wide range of personal properties, such as identity, gender, and emotion, that are available in a person’s movements. The movements from a total of 30 nonprofessional actors (15 of them female) were captured while they performed walking, knocking, lifting, and throwing actions, as well as their combination in angry, happy, neutral, and sad affective styles. From the raw motion capture data, a library of 4,080 movements was obtained, using techniques based on Character Studio (plug-ins for 3D Studio MAX, AutoDesk, Inc.), MATLAB (The Math Works, Inc.), or a combination of these two. For the knocking, lifting, and throwing actions, 10 repetitions of the simple action unit were obtained for each affect, and for the other actions, two longer movement recordings were obtained for each affect. We discuss the potential use of the library for computational and behavioral analyses of movement variability, of human character animation, and of how gender, emotion, and identity are encoded and decoded from human movement.

Item Type: Article
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Science > Research Groups > Norwich Epidemiology Centre
Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre
Faculty of Science > Research Groups > Data Science and AI
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 05 Jan 2023 11:30
Last Modified: 10 Dec 2024 01:41
URI: https://ueaeprints.uea.ac.uk/id/eprint/90416
DOI: 10.3758/BF03192758

Actions (login required)

View Item View Item