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Pattern Analysis and Applications
Erschienen in: Pattern Analysis and Applications 2/2009

01.06.2009 | Theoretical Advances

Human tracking and silhouette extraction for human–robot interaction systems

verfasst von: Jung-Ho Ahn, Cheolmin Choi, Sooyeong Kwak, Kilcheon Kim, Hyeran Byun

Erschienen in: Pattern Analysis and Applications | Ausgabe 2/2009

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Abstract

In this study, we propose a new integrated computer vision system designed to track multiple human beings and extract their silhouette with a pan-tilt stereo camera, so that it can assist in gesture and gait recognition in the field of Human–Robot Interaction (HRI). The proposed system consists of three modules: detection, tracking and silhouette extraction. These modules are robust to camera movements, and they work interactively in near real-time. Detection was performed by camera ego-motion compensation and disparity segmentation. For tracking, we present an efficient mean shift-based tracking method in which the tracking objects are characterized as disparity weighted color histograms. The silhouette was obtained by two-step segmentation. A trimap was estimated in advance and then effectively incorporated into the graph-cut framework for fine segmentation. The proposed system was evaluated with respect to ground truth data, and it was shown to detect and track multiple people very well and also produce high-quality silhouettes.
Vorheriger Artikel On Bayesian analysis of a finite generalized Dirichlet mixture via a Metropolis-within-Gibbs sampling
Nächster Artikel A multi-scale template method for shape detection with bio-medical applications

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Metadaten
Titel
Human tracking and silhouette extraction for human–robot interaction systems
verfasst von
Jung-Ho Ahn
Cheolmin Choi
Sooyeong Kwak
Kilcheon Kim
Hyeran Byun
Publikationsdatum
01.06.2009
Verlag
Springer-Verlag
Erschienen in
Pattern Analysis and Applications / Ausgabe 2/2009
Print ISSN: 1433-7541
Elektronische ISSN: 1433-755X
DOI
https://doi.org/10.1007/s10044-008-0112-3

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