Output details
11 - Computer Science and Informatics
Kingston University
Article title
Integration of bottom-up/top-down approaches for 2D pose estimation using probabilistic Gaussian modelling
Type
D - Journal article
Title of journal
Computer Vision and Image Understanding
Article number
-
Volume number
115
Issue number
2
First page of article
242
ISSN of journal
1077-3142
Year of publication
2011
Number of additional authors
2
Additional information
<23> This work dealt with the challenging problem of 2D pose estimation on single frames, based on the integration of probabilistic bottom-up and top-down processes which iteratively refine each other. The main advantage of the presented framework is its activity-independency since it does not rely on learning any motion model.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
4
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
