Clustering of human actions using invariant body shape descriptor and dynamic time warping

Massimiliano Pierobon, Marco Marcon, Augusto Sarti, Stefano Tubaro

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

16 Scopus citations

Abstract

We propose a human action clustering method based on a 3D representation of the body in terms of volumetric coordinates. Features representing body postures are extracted directly from 3D data, making the system inherently insensitive to viewpoint dependence, motion ambiguities and self-occlusions. An Invariant Shape Descriptor of human body is obtained in order to capture only posture-dependent characteristics, despite possible differences in translation, orientation, scale and body size. Frame-by-frame descriptions, generated from a gesture sequence, are collected together in matrices. Clustering of action matrices is eventually performed, and through a Dynamic Time Warping (while computing the distance metric), we gain independence from possible temporal nonlinear distortions among different instances of the same gesture.

Original languageEnglish (US)
Title of host publicationIEEE Conference on Advanced Video and Signal Based Based Surveillance - Proceedings of AVSS 2005
Pages22-27
Number of pages6
DOIs
StatePublished - 2005
EventIEEE Conference on Advanced Video and Signal Based Surveillance, AVSS 2005 - Como, Italy
Duration: Sep 15 2005Sep 16 2005

Publication series

NameIEEE International Conference on Advanced Video and Signal Based Surveillance - Proceedings of AVSS 2005
Volume2005

Other

OtherIEEE Conference on Advanced Video and Signal Based Surveillance, AVSS 2005
CountryItaly
CityComo
Period9/15/059/16/05

ASJC Scopus subject areas

  • Engineering(all)

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    Pierobon, M., Marcon, M., Sarti, A., & Tubaro, S. (2005). Clustering of human actions using invariant body shape descriptor and dynamic time warping. In IEEE Conference on Advanced Video and Signal Based Based Surveillance - Proceedings of AVSS 2005 (pp. 22-27). [1577237] (IEEE International Conference on Advanced Video and Signal Based Surveillance - Proceedings of AVSS 2005; Vol. 2005). https://doi.org/10.1109/AVSS.2005.1577237