loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Second IEEE International Conference on Automatic Face and Gesture Recognition (FG '96)
Towards 3D hand tracking using a deformable model
Killington, Vermont
October 14-October 16
ISBN: 0-8186-7713-9
ASCII Text
x 
 
T. Heap, D. Hogg, "Towards 3D hand tracking using a deformable model," Automatic Face and Gesture Recognition, IEEE International Conference on, pp. 140, Second IEEE International Conference on Automatic Face and Gesture Recognition (FG '96), 1996.
 
 
BibTex
x
 
@article{ 10.1109/AFGR.1996.557255,
author = {T. Heap and D. Hogg},
title = {Towards 3D hand tracking using a deformable model},
journal ={Automatic Face and Gesture Recognition, IEEE International Conference on},
volume = {0},
year = {1996},
isbn = {0-8186-7713-9},
pages = {140},
doi = {http://doi.ieeecomputersociety.org/10.1109/AFGR.1996.557255},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Automatic Face and Gesture Recognition, IEEE International Conference on
TI - Towards 3D hand tracking using a deformable model
SN - 0-8186-7713-9
SP
EP
A1 - T. Heap,
A1 - D. Hogg,
PY - 1996
KW - tracking; 3D hand tracking; deformable model; Point Distribution Model; human hand; training data; weighted least-squares pose parameter; computational cost
VL - 0
JA - Automatic Face and Gesture Recognition, IEEE International Conference on
ER -
 
T. Heap, Sch. of Comput. Studies, Leeds Univ., UK
D. Hogg, Sch. of Comput. Studies, Leeds Univ., UK
In this paper we first describe how we have constructed a 3D deformable Point Distribution Model of the human hand, capturing training data semi-automatically from volume images via a physically-based model. We then show how we have attempted to use this model in tracking an unmarked hand moving with 6 degrees of freedom (plus deformation) in real time using a single video camera. In the course of this we show how to improve on a weighted least-squares pose parameter approximation at little computational cost. We note the successes and shortcomings of our system and discuss how it might be improved.
Index Terms:
tracking; 3D hand tracking; deformable model; Point Distribution Model; human hand; training data; weighted least-squares pose parameter; computational cost
Citation:
T. Heap, D. Hogg, "Towards 3D hand tracking using a deformable model," fg, pp.140, Second IEEE International Conference on Automatic Face and Gesture Recognition (FG '96), 1996
Usage of this product signifies your acceptance of the Terms of Use.