Data fusion for 3D gestures tracking using a camera mounted on a robot

Paulo Menezes, Frédéric Lerasle, Jorge Dias

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

This article describes a multiple feature data fusion applied to an auxiliary particle filter for markerless tracking of 3D two-arm gestures by using a single camera mounted on a mobile robot. The human limbs are modelled by a set of linked degenerated quadrics which are truncated by pairs of planes also modelled as degenerated quadrics. The method relies on the projection of both the model's silhouette and local features located on the model surface, to validate the particles (associated configurations) which generate the best model-to-image fittings. Our cost metric combines robustly two imaging cues i.e. model contours and colour or texture based patches located on the model surface, subject to 3D joint limits and also non self-intersection constraints. The results show the robustness and versatility of our data fusion based approach.

Original languageBritish English
Title of host publicationProceedings - 18th International Conference on Pattern Recognition, ICPR 2006
Pages464-467
Number of pages4
DOIs
StatePublished - 2006
Event18th International Conference on Pattern Recognition, ICPR 2006 - Hong Kong, China
Duration: 20 Aug 200624 Aug 2006

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume1
ISSN (Print)1051-4651

Conference

Conference18th International Conference on Pattern Recognition, ICPR 2006
Country/TerritoryChina
CityHong Kong
Period20/08/0624/08/06

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