3D pictorial structures for multiple view articulated pose estimation
2013 (English)In: 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE Computer Society, 2013, 3618-3625 p.Conference paper (Refereed)
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.
Place, publisher, year, edition, pages
IEEE Computer Society, 2013. 3618-3625 p.
, IEEE Conference on Computer Vision and Pattern Recognition. Proceedings, ISSN 1063-6919
human pose estimation, motion capture, multiple view 3D reconstruction, part-based models, pictorial structures
Engineering and Technology Computer Systems
IdentifiersURN: urn:nbn:se:kth:diva-129706DOI: 10.1109/CVPR.2013.464ISI: 000331094303088ScopusID: 2-s2.0-84887329445OAI: oai:DiVA.org:kth-129706DiVA: diva2:653207
26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013; Portland, OR; United States; 23 June 2013 through 28 June 2013
QC 201310072013-10-032013-10-032014-03-24Bibliographically approved