Real-time 3D body pose estimation

(Echtzeiterkennung von Körperposen in 3D)

This chapter presents a novel approach to markerless real-time 3D pose estimation in a multi camera setup. We explain how foreground-background segmentation and 3D reconstruction are used to extract a 3D hull of the user. This is done in real-time using voxel carving and a fixed lookup table. The body pose is then retrieved using an example-based classifierr which uses 3D Haar-like wavelet features to allow for real-time classification. Average Neighborhood Margin Maximization (ANMM) is introduced as a powerful approach to train these Haar-like features.
© Copyright 2009 Multi-Camera Networks: Concepts and Applications. Veröffentlicht von Elsevier. Alle Rechte vorbehalten.

Bibliographische Detailangaben
Schlagworte:
Notationen:Naturwissenschaften und Technik
Tagging:markerless
Veröffentlicht in:Multi-Camera Networks: Concepts and Applications
Sprache:Englisch
Veröffentlicht: Elsevier 2009
Online-Zugang:http://www.mvdblive.org/research/eth_biwi_00612.pdf
Seiten:335-360
Dokumentenarten:Artikel
Level:hoch