3D Pictorial Structures for Multiple View Articulated Pose Estimation

We consider the problem of automatically estimating the 3D pose of humans from images, taken from multiple calibrated views. We show that it is possible and tractable to extend the pictorial structures framework, popular for 2D pose estimation, to 3D. We discuss how to use this framework to impose v...

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Bibliographic Details
Published in:2013 IEEE Conference on Computer Vision and Pattern Recognition pp. 3618 - 3625
Main Authors: Burenius, Magnus, Sullivan, Josephine, Carlsson, Stefan
Format: Conference Proceeding
Language:English
Published: IEEE 01.06.2013
Subjects:
Cameras
Dynamic programming
Estimation
human pose estimation
Joints
motion capture
multiple view 3D reconstruction
part-based models
pictorial structures
Three-dimensional displays
Tree graphs
ISSN:1063-6919, 1063-6919
Online Access:Get full text
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Summary:We consider the problem of automatically estimating the 3D pose of humans from images, taken from multiple calibrated views. We show that it is possible and tractable to extend the pictorial structures framework, popular for 2D pose estimation, to 3D. We discuss how to use this framework to impose view, skeleton, joint angle and intersection constraints in 3D. The 3D pictorial structures are evaluated on multiple view data from a professional football game. The evaluation is focused on computational tractability, but we also demonstrate how a simple 2D part detector can be plugged into the framework.
ISSN:1063-6919
1063-6919
DOI:10.1109/CVPR.2013.464