3D Pictorial Structures for Multiple View Articulated Pose Estimation
- 1 June 2013
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE) in 2013 IEEE Conference on Computer Vision and Pattern Recognition
- p. 3618-3625
- https://doi.org/10.1109/cvpr.2013.464
Abstract
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.Keywords
This publication has 12 references indexed in Scilit:
- Motion capture from dynamic orthographic camerasPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Discriminative Appearance Models for Pictorial StructuresInternational Journal of Computer Vision, 2011
- Loose-limbed People: Estimating 3D Human Pose and Motion Using Non-parametric Belief PropagationInternational Journal of Computer Vision, 2011
- Articulated pose estimation with flexible mixtures-of-partsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Object Detection with Discriminatively Trained Part-Based ModelsIEEE Transactions on Pattern Analysis and Machine Intelligence, 2009
- A Study of Parts-Based Object Class Detection Using Complete GraphsInternational Journal of Computer Vision, 2009
- Measure Locally, Reason Globally: Occlusion-sensitive Articulated Pose EstimationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- Histograms of Oriented Gradients for Human DetectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Pictorial Structures for Object RecognitionInternational Journal of Computer Vision, 2005
- Practical Parameterization of Rotations Using the Exponential MapJournal of Graphics Tools, 1998