loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
18th International Conference on Pattern Recognition (ICPR'06) Volume 2
Human Tracking by Particle Filtering Using Full 3D Model of Both Target and Environment
Hong Kong
August 20-August 24
ISBN: 0-7695-2521-0
ASCII Text
x 
 
Tatsuya Osawa, Xiaojun Wu, Kaoru Wakabayashi, Takayuki Yasuno, "Human Tracking by Particle Filtering Using Full 3D Model of Both Target and Environment," Pattern Recognition, International Conference on, vol. 2, pp. 25-28, 18th International Conference on Pattern Recognition (ICPR'06) Volume 2, 2006.
 
 
BibTex
x
 
@article{ 10.1109/ICPR.2006.641,
author = {Tatsuya Osawa and Xiaojun Wu and Kaoru Wakabayashi and Takayuki Yasuno},
title = {Human Tracking by Particle Filtering Using Full 3D Model of Both Target and Environment},
journal ={Pattern Recognition, International Conference on},
volume = {2},
year = {2006},
issn = {1051-4651},
pages = {25-28},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.641},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Pattern Recognition, International Conference on
TI - Human Tracking by Particle Filtering Using Full 3D Model of Both Target and Environment
SN - 1051-4651
SP25
EP28
A1 - Tatsuya Osawa,
A1 - Xiaojun Wu,
A1 - Kaoru Wakabayashi,
A1 - Takayuki Yasuno,
PY - 2006
VL - 2
JA - Pattern Recognition, International Conference on
ER -
 
Tatsuya Osawa, NTT Cyber Space Laboratories, NTT corporation, Japan
Xiaojun Wu, NTT Cyber Space Laboratories, NTT corporation, Japan
Kaoru Wakabayashi, NTT Cyber Space Laboratories, NTT corporation, Japan
Takayuki Yasuno, NTT Cyber Space Laboratories, NTT corporation, Japan
This work presents a new approach based on particle filtering to directly estimate the 3D positions of humans. Our system can predict occlusions due to other movements because we track humans in a 3D space, not on a 2D image plane. In addition, we introduce a 3D environmental model as the background model for tracking. This makes it easier to handle occlusions due to fixed objects in the environment. The 3D environmental model is automatically constructed by our original method from video sequences. Experiments show that our system is stable under occlusions due to the movements of both other subjects and fixed objects.
Citation:
Tatsuya Osawa, Xiaojun Wu, Kaoru Wakabayashi, Takayuki Yasuno, "Human Tracking by Particle Filtering Using Full 3D Model of Both Target and Environment," icpr, vol. 2, pp.25-28, 18th International Conference on Pattern Recognition (ICPR'06) Volume 2, 2006
Usage of this product signifies your acceptance of the Terms of Use.