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Machine Vision and Applications

Erschienen in:

01.01.2015 | Original Paper

Tracking the articulated motion of the human body with two RGBD cameras

verfasst von: Damien Michel, Costas Panagiotakis, Antonis A. Argyros

Erschienen in: Machine Vision and Applications | Ausgabe 1/2015

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Abstract

We present a model-based, top-down solution to the problem of tracking the 3D position, orientation and full articulation of the human body from markerless visual observations obtained by two synchronized RGBD cameras. Inspired by recent advances to the problem of model-based hand tracking Oikonomidis et al. (Efficient Model-based 3D Tracking of Hand Articulations using Kinect, 2011), we treat human body tracking as an optimization problem that is solved using stochastic optimization techniques. We show that the proposed approach outperforms in accuracy state of the art methods that rely on a single RGBD camera. Thus, for applications that require increased accuracy and can afford the extra-complexity introduced by the second sensor, the proposed approach constitutes a viable solution to the problem of markerless human motion tracking. Our findings are supported by an extensive quantitative evaluation of the method that has been performed on a publicly available data set that is annotated with ground truth.

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Titel: Tracking the articulated motion of the human body with two RGBD cameras
verfasst von: Damien Michel
Costas Panagiotakis
Antonis A. Argyros
Publikationsdatum: 01.01.2015
Verlag: Springer Berlin Heidelberg
Erschienen in: Machine Vision and Applications / Ausgabe 1/2015
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI: https://doi.org/10.1007/s00138-014-0651-0

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