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A very simple framework for 3D human poses estimation using a single 2D image: Comparison of geometric moments descriptors.

Atrevi, Dieudonné Fabrice and Vivet, Damien and Duculty, Florent and Emile, Bruno A very simple framework for 3D human poses estimation using a single 2D image: Comparison of geometric moments descriptors. (2017) Pattern Recognition, 71. 389-401. ISSN 0031-3203

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Official URL: http://dx.doi.org/10.1016/j.patcog.2017.06.024

Abstract

In this paper, we propose a framework in order to automatically extract the 3D pose of an individual from a single silhouette image obtained with a classical low-cost camera without any depth information. By pose, we mean the configuration of human bones in order to reconstruct a 3D skeleton representing the 3D posture of the detected human. Our approach combines prior learned correspondences between silhouettes and skeletons extracted from simulated 3D human models publicly available on the internet. The main advantages of such approach are that silhouettes can be very easily extracted from video, and 3D human models can be animated using motion capture data in order to quickly build any movement training data. In order to match detected silhouettes with simulated silhouettes, we compared geometrics invariants moments. According to our results, we show that the proposed method provides very promising results with a very low time processing.

Item Type:Article
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
Other partners > Ecole Nationale Supérieure d'Ingénieurs de Bourges - ENSI Bourges (FRANCE)
Other partners > Université d'Orléans (FRANCE)
Laboratory name:
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Deposited By: Damien Vivet
Deposited On:27 Sep 2017 12:00

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