Journal article icon

Journal article

Upper body detection and tracking in extended signing sequences

Abstract:

The goal of this work is to detect and track the articulated pose of a human in signing videos of more than one hour in length. In particular we wish to accurately localise hands and arms, despite fast motion and a cluttered and changing background.

We cast the problem as inference in a generative model of the image, and propose a complete model which accounts for self-occlusion of the arms. Under this model, limb detection is expensive due to the very large number of possible config...

Expand abstract
Publication status:
Published
Peer review status:
Peer reviewed

Actions


Access Document


Publisher copy:
10.1007/s11263-011-0480-9

Authors


More by this author
Institution:
University of Oxford
Department:
Mathematical,Physical & Life Sciences Division - Engineering Science
Role:
Author
More by this author
Institution:
University of Leeds
Department:
School of Computing
Role:
Author
More by this author
Institution:
Cornell University, Cornell, USA
Department:
Computer Science Department
Role:
Author
More by this author
Institution:
University of Oxford
Department:
Mathematical,Physical & Life Sciences Division - Engineering Science
Role:
Author
Engineering and Physical Sciences Research Council More from this funder
Royal Academy of Engineering More from this funder
More from this funder
Grant:
VisRec No. 228180
Publisher:
Springer Publisher's website
Journal:
International Journal of Computer Vision Journal website
Volume:
95
Issue:
2
Pages:
180-197
Publication date:
2011-01-01
DOI:
EISSN:
1573-1405
ISSN:
0920-5691
URN:
uuid:41643af0-bb8b-4f18-a696-22eb623ce70c
Local pid:
ora:5835

Terms of use


Metrics


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP