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Illumination-robust people tracking using a smart camera network

Bo Bo Nyan UGent, Peter Van Hese, Junzhi Guan UGent, Sebastian Grünwedel, Jorge Niño Castañeda UGent, Dimitri Van Cauwelaert UGent, Dirk Van Haerenborgh, Peter Veelaert UGent and Wilfried Philips UGent (2014) Proceedings of SPIE. 9025.
abstract
Many computer vision based applications require reliable tracking of multiple people under unpredictable lighting conditions. Many existing trackers do not handle illumination changes well, especially sudden changes in illumination. This paper presents a system to track multiple people reliably even under rapid illumination changes using a network of calibrated smart cameras with overlapping views. Each smart camera extracts foreground features by detecting texture changes between the current image and a static background image. The foreground features belonging to each person are tracked locally on each camera but these local estimates are sent to a fusion center which combines them to generate more accurate estimates. The final estimates are fed back to all smart cameras, which use them as prior information for tracking in the next frame. The texture based approach makes our method very robust to illumination changes. We tested the performance of our system on six video sequences, some containing sudden illumination changes and up to four walking persons. The results show that our tracker can track multiple people accurately with an average tracking error as low as 8 cm even when the illumination varies rapidly. Performance comparison to a state-of-the-art tracking system shows that our method outperforms.
Please use this url to cite or link to this publication:
author
organization
year
type
conference (proceedingsPaper)
publication status
published
subject
keyword
data fusion, feature subtraction, illumination-robustness, Multi-camera tracking
in
Proceedings of SPIE
editor
J Roning and D Casasent
volume
9025
issue title
INTELLIGENT ROBOTS AND COMPUTER VISION XXXI: ALGORITHMS AND TECHNIQUES
article number
90250G
pages
10 pages
publisher
IS&T/SPIE
place of publication
San Francisco, California, USA
conference name
Conference on Intelligent Robots and Computer Vision XXXI - Algorithms and Techniques
conference location
San Francisco, California, USA
conference start
2014-02-04
conference end
2014-02-06
Web of Science type
Proceedings Paper
Web of Science id
000334023700012
ISSN
0277-786X
ISBN
9780819499424
DOI
10.1117/12.2036764
language
English
UGent publication?
yes
classification
P1
copyright statement
I have transferred the copyright for this publication to the publisher
id
4289321
handle
http://hdl.handle.net/1854/LU-4289321
date created
2014-02-12 16:33:01
date last changed
2017-01-02 09:53:19
@inproceedings{4289321,
  abstract     = {Many computer vision based applications require reliable tracking of multiple people under unpredictable lighting conditions. Many existing trackers do not handle illumination changes well, especially sudden changes in illumination. This paper presents a system to track multiple people reliably even under rapid illumination changes using a network of calibrated smart cameras with overlapping views. Each smart camera extracts foreground features by detecting texture changes between the current image and a static background image. The foreground features belonging to each person are tracked locally on each camera but these local estimates are sent to a fusion center which combines them to generate more accurate estimates. The final estimates are fed back to all smart cameras, which use them as prior information for tracking in the next frame. The texture based approach makes our method very robust to illumination changes. We tested the performance of our system on six video sequences, some containing sudden illumination changes and up to four walking persons. The results show that our tracker can track multiple people accurately with an average tracking error as low as 8 cm even when the illumination varies rapidly. Performance comparison to a state-of-the-art tracking system shows that our method outperforms.},
  articleno    = {90250G},
  author       = {Nyan, Bo Bo and Van Hese, Peter and Guan, Junzhi and Gr{\"u}nwedel, Sebastian and Ni{\~n}o Casta{\~n}eda, Jorge and Van Cauwelaert, Dimitri and Van Haerenborgh, Dirk and Veelaert, Peter and Philips, Wilfried},
  booktitle    = {Proceedings of SPIE},
  editor       = {Roning, J and Casasent, D },
  isbn         = {9780819499424},
  issn         = {0277-786X},
  keyword      = {data fusion,feature subtraction,illumination-robustness,Multi-camera tracking},
  language     = {eng},
  location     = {San Francisco, California, USA},
  pages        = {10},
  publisher    = {IS\&T/SPIE},
  title        = {Illumination-robust people tracking using a smart camera network},
  url          = {http://dx.doi.org/10.1117/12.2036764},
  volume       = {9025},
  year         = {2014},
}

Chicago
Nyan, Bo Bo, Peter Van Hese, Junzhi Guan, Sebastian Grünwedel, Jorge Niño Castañeda, Dimitri Van Cauwelaert, Dirk Van Haerenborgh, Peter Veelaert, and Wilfried Philips. 2014. “Illumination-robust People Tracking Using a Smart Camera Network.” In Proceedings of SPIE, ed. J Roning and D Casasent. Vol. 9025. San Francisco, California, USA: IS&T/SPIE.
APA
Nyan, B. B., Van Hese, P., Guan, J., Grünwedel, S., Niño Castañeda, J., Van Cauwelaert, D., Van Haerenborgh, D., et al. (2014). Illumination-robust people tracking using a smart camera network. In J. Roning & D. Casasent (Eds.), Proceedings of SPIE (Vol. 9025). Presented at the Conference on Intelligent Robots and Computer Vision XXXI - Algorithms and Techniques, San Francisco, California, USA: IS&T/SPIE.
Vancouver
1.
Nyan BB, Van Hese P, Guan J, Grünwedel S, Niño Castañeda J, Van Cauwelaert D, et al. Illumination-robust people tracking using a smart camera network. In: Roning J, Casasent D, editors. Proceedings of SPIE. San Francisco, California, USA: IS&T/SPIE; 2014.
MLA
Nyan, Bo Bo, Peter Van Hese, Junzhi Guan, et al. “Illumination-robust People Tracking Using a Smart Camera Network.” Proceedings of SPIE. Ed. J Roning & D Casasent. Vol. 9025. San Francisco, California, USA: IS&T/SPIE, 2014. Print.