Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICIP.2005.1530631
Title: Human body posture refinement by nonparametric belief propagation
Authors: Wang, R.
Leow, W.K. 
Issue Date: 2005
Source: Wang, R.,Leow, W.K. (2005). Human body posture refinement by nonparametric belief propagation. Proceedings - International Conference on Image Processing, ICIP 3 : 1272-1275. ScholarBank@NUS Repository. https://doi.org/10.1109/ICIP.2005.1530631
Abstract: Accurate human body posture refinement from single or multiple images is essential in many applications. Two main causes of difficulty to solve the refinement problem are high degree freedom of human body and self-occlusion. One of the most recent algorithms is nonparametric belief propagation (NBP) that solves the problem in a lower dimensional state space. However, it is difficult to handle self-occlusion. This paper presents an NBP-based algorithm that can refine body posture even in self-occlusion case, which has been shown by experimental results. The experimental results also show that our algorithm can accurately refine body posture even if the initial posture has large difference from the true posture. © 2005 IEEE.
Source Title: Proceedings - International Conference on Image Processing, ICIP
URI: http://scholarbank.nus.edu.sg/handle/10635/40260
ISBN: 0780391349
ISSN: 15224880
DOI: 10.1109/ICIP.2005.1530631
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

3
checked on Dec 11, 2017

Page view(s)

48
checked on Dec 16, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.