Abstract
Over recent years, the fall in cost, and increased availability of motion capture equipment has led to an increase in non-specialist companies being able to use motion capture data to guide animation sequences for computer games and other applications. [1] A bottleneck in the animation production process is in the clean-up of capture sessions to remove and/or correct anomalous (unusable) frames and noise. In this paper an investigation is carried out into whether the 2-layer SOM network previously designed [5] and trained on one capture session, can be used to create a neural classifier to be used to classify another separate capture session.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Geroch, M.: Motion Capture for the Rest of us. Journal of Computing Sciences in Colleges 19(3), 157–164 (2004)
Gibson, D., Campbell, N., Dalton, C., Thomas, B.: Extraction of Motion Data from Image Sequences to Assist Animators. In: Proceedings of the British Machine Vision Conference (2000)
Kovar, L., Gleicher, M.: Automated Extraction and Parameterization of Motions in Large Data Sets. ACM Transactions on Graphics 23(3), 559–568 (2004)
Miller, I., McGlinchey, S.: Automating the Clean-up Process of Magnetic Motion Capture Systems. In: Proceedings of the Game Design and Technology Workshop (2005)
Miller, I., McGlinchey, S., Chaperot, B.: Anomaly Detection in Magnetic Motion Capture using a 2-Layer SOM network. In: Proceedings of IEEE Conference of Computational Intelligence in Games 2006 (May 2006) (to appear)
Müller, M., Röder, T., Clausen, M.: Efficient Content-Based Retrieval of Motion Capture Data. ACM Transactions on Graphics 24(3), 677–685 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 IFIP International Federation for Information Processing
About this paper
Cite this paper
Miller, I., McGlinchey, S. (2006). A Neural Classifier for Anomaly Detection in Magnetic Motion Capture. In: Harper, R., Rauterberg, M., Combetto, M. (eds) Entertainment Computing - ICEC 2006. ICEC 2006. Lecture Notes in Computer Science, vol 4161. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11872320_17
Download citation
DOI: https://doi.org/10.1007/11872320_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45259-1
Online ISBN: 978-3-540-45261-4
eBook Packages: Computer ScienceComputer Science (R0)