Ghent University Academic Bibliography

Advanced

Real-time multi-colourspace hand segmentation

Vincent Spruyt, Alessandro Ledda and Stig Geerts (2010) IEEE International Conference on Image Processing ICIP. p.3117-3120
abstract
This paper proposes an accurate real-time hand tracking and segmentation algorithm. A particle filter tracks the hands in time, based on colour and motion cues. This filter is able to automatically recover from failures and does not need an initialization phase. The algorithm is proven to be robust against lighting changes, and can be used in unconstrained environments. Hand segmentation is based on a Gaussian Mixture Model and refined using a combination of spatial information. Cues from both HSV and RGB colour space are used to increase robustness.
Please use this url to cite or link to this publication:
author
organization
year
type
conference (proceedingsPaper)
publication status
published
subject
keyword
hand tracking, hand segmentation, hand detection
in
IEEE International Conference on Image Processing ICIP
issue title
2010 IEEE international conference on image processing
pages
3117 - 3120
publisher
IEEE
place of publication
New York, NY, USA
conference name
2010 IEEE 17th International conference on Image Processing (ICIP 2010)
conference location
Hong Kong, PR China
conference start
2010-09-26
conference end
2010-09-29
Web of Science type
Proceedings Paper
Web of Science id
000287728003049
ISSN
1522-4880
ISBN
9781424479948
9781424479924
DOI
10.1109/ICIP.2010.5653220
language
English
UGent publication?
yes
classification
P1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1156821
handle
http://hdl.handle.net/1854/LU-1156821
date created
2011-02-20 20:59:41
date last changed
2017-01-02 09:52:27
@inproceedings{1156821,
  abstract     = {This paper proposes an accurate real-time hand tracking and segmentation algorithm. A particle filter tracks the hands in time, based on colour and motion cues. This filter is able to automatically recover from failures and does not need an initialization phase. The algorithm is proven to be robust against lighting changes, and can be used in unconstrained environments. Hand segmentation is based on a Gaussian Mixture Model and refined using a combination of spatial information. Cues from both HSV and RGB colour space are used to increase robustness.},
  author       = {Spruyt, Vincent and Ledda, Alessandro and Geerts, Stig},
  booktitle    = {IEEE International Conference on Image Processing ICIP},
  isbn         = {9781424479948},
  issn         = {1522-4880},
  keyword      = {hand tracking,hand segmentation,hand detection},
  language     = {eng},
  location     = {Hong Kong, PR China},
  pages        = {3117--3120},
  publisher    = {IEEE},
  title        = {Real-time multi-colourspace hand segmentation},
  url          = {http://dx.doi.org/10.1109/ICIP.2010.5653220},
  year         = {2010},
}

Chicago
Spruyt, Vincent, Alessandro Ledda, and Stig Geerts. 2010. “Real-time Multi-colourspace Hand Segmentation.” In IEEE International Conference on Image Processing ICIP, 3117–3120. New York, NY, USA: IEEE.
APA
Spruyt, V., Ledda, A., & Geerts, S. (2010). Real-time multi-colourspace hand segmentation. IEEE International Conference on Image Processing ICIP (pp. 3117–3120). Presented at the 2010 IEEE 17th International conference on Image Processing (ICIP 2010), New York, NY, USA: IEEE.
Vancouver
1.
Spruyt V, Ledda A, Geerts S. Real-time multi-colourspace hand segmentation. IEEE International Conference on Image Processing ICIP. New York, NY, USA: IEEE; 2010. p. 3117–20.
MLA
Spruyt, Vincent, Alessandro Ledda, and Stig Geerts. “Real-time Multi-colourspace Hand Segmentation.” IEEE International Conference on Image Processing ICIP. New York, NY, USA: IEEE, 2010. 3117–3120. Print.