3D pictorial structures for multiple human pose estimation

Belagiannis V, Amin S, Andriluka M, Schiele B, Navab N, Ilic S (2014)

Publication Type: Conference contribution

Publication year: 2014

Journal

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition IEEE Computer Society; 1999

Publisher: IEEE Computer Society

Pages Range: 1669-1676

Conference Proceedings Title: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Event location: Columbus, OH, USA

ISBN: 9781479951178

DOI: 10.1109/CVPR.2014.216

Abstract

In this work, we address the problem of 3D pose estimation of multiple humans from multiple views. This is a more challenging problem than single human 3D pose estimation due to the much larger state space, partial occlusions as well as across view ambiguities when not knowing the identity of the humans in advance. To address these problems, we first create a reduced state space by triangulation of corresponding body joints obtained from part detectors in pairs of camera views. In order to resolve the ambiguities of wrong and mixed body parts of multiple humans after triangulation and also those coming from false positive body part detections, we introduce a novel 3D pictorial structures (3DPS) model. Our model infers 3D human body configurations from our reduced state space. The 3DPS model is generic and applicable to both single and multiple human pose estimation. In order to compare to the state-of-the art, we first evaluate our method on single human 3D pose estimation on HumanEva-I [22] and KTH Multiview Football Dataset II [8] datasets. Then, we introduce and evaluate our method on two datasets for multiple human 3D pose estimation.

Authors with CRIS profile

Vasileios Belagiannis

Involved external institutions

Technische Universität München (TUM) DE Germany (DE) Max Planck Institute for Informatics / Max-Planck-Institut für Informatik DE Germany (DE)

How to cite

APA:

Belagiannis, V., Amin, S., Andriluka, M., Schiele, B., Navab, N., & Ilic, S. (2014). 3D pictorial structures for multiple human pose estimation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 1669-1676). Columbus, OH, USA: IEEE Computer Society.

MLA:

Belagiannis, Vasileios, et al. "3D pictorial structures for multiple human pose estimation." Proceedings of the 27th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014, Columbus, OH, USA IEEE Computer Society, 2014. 1669-1676.

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