Automated gesture segmentation from dance sequences

Kanav Kahol, Priyamvada Tripathi, Sethuraman Panchanathan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

78 Scopus citations

Abstract

Complex human motion (e.g. dance) sequences are typically analyzed by segmenting them into shorter motion sequences, called gestures. However, this segmentation process is subjective, and varies considerably from one choreographer to another. Dance sequences also exhibit a large vocabulary of gestures. In this paper, we propose an algorithm called Hierarchical Activity Segmentation. This algorithm employs a dynamic hierarchical layered structure to represent human anatomy, and uses low-level motion parameters to characterize motion in the various layers of this hierarchy, which correspond to different segments of the human body. This characterization is used with a naïve, Bayesian classifier to derive choreographer profiles from empirical data that are used to predict how particular choreographers will segment gestures in other motion sequences. When the predictions were tested with a library of 45 3D motion capture sequences (with 185 distinct gestures) created by 5 different choreographers, they were found to be 93.3% accurate.

Original languageEnglish (US)
Title of host publicationProceedings - Sixth IEEE International Conference on Automatic Face and Gesture Recognition FGR 2004
Pages883-888
Number of pages6
DOIs
StatePublished - Sep 24 2004
EventProceedings - Sixth IEEE International Conference on Automatic Face and Gesture Recognition FGR 2004 - Seoul, Korea, Republic of
Duration: May 17 2004May 19 2004

Publication series

NameProceedings - Sixth IEEE International Conference on Automatic Face and Gesture Recognition

Other

OtherProceedings - Sixth IEEE International Conference on Automatic Face and Gesture Recognition FGR 2004
CountryKorea, Republic of
CitySeoul
Period5/17/045/19/04

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Kahol, K., Tripathi, P., & Panchanathan, S. (2004). Automated gesture segmentation from dance sequences. In Proceedings - Sixth IEEE International Conference on Automatic Face and Gesture Recognition FGR 2004 (pp. 883-888). (Proceedings - Sixth IEEE International Conference on Automatic Face and Gesture Recognition). https://doi.org/10.1109/AFGR.2004.1301645