Open Access
Issue
MATEC Web of Conferences
Volume 54, 2016
2016 7th International Conference on Mechanical, Industrial, and Manufacturing Technologies (MIMT 2016)
Article Number 08003
Number of page(s) 7
Section Image processing and visualization
DOI https://doi.org/10.1051/matecconf/20165408003
Published online 22 April 2016
  1. Goyette, Nil, Pierre-Marc Jodoin, Fatih Porikli, Janusz Konrad, and Prakash Ishwar. “Changedetection. net: A new change detection benchmark dataset.” In Computer Vision and Pattern Recognition Workshops (CVPRW), 2012 IEEE Computer Society Conference on, pp. 1-8. IEEE, 2012.
  2. Bouwmans, Thierry. “Traditional and recent approaches in background modeling for foreground detection: An overview.” Computer Science Review 11 (2014): 31-66. [CrossRef]
  3. Barnich, Olivier, and Marc Van Droogenbroeck. “ViBe: A universal background subtraction algorithm for video sequences.” Image Processing, IEEE Transactions on 20, no. 6 (2011): 1709-1724. [CrossRef]
  4. Stauffer, Chris, and W. Eric L. Grimson. “Adaptive background mixture models for real-time tracking.” In Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on., vol. 2. IEEE, 1999.
  5. Elgammal, Ahmed, Davis Harwood, and Larry David. “Non-parametric model for background subtraction.” In Computer Vision—ECCV 2000, pp. 751-767. Springer Berlin Heidelberg, 2000. [CrossRef]
  6. Kim, Kyungnam, Thanarat H. Chalidabhongse, David Harwood, and Larry Davis. “Real-time foreground–background segmentation using codebook model.” Real-time imaging 11, no. 3 (2005): 172-185. [CrossRef]
  7. Sheikh, Yaser, and Mubarak Shah. “Bayesian modeling of dynamic scenes for object detection.” Pattern Analysis and Machine Intelligence, IEEE Transactions on 27, no. 11 (2005): 1778-1792. [CrossRef]
  8. St-Charles, Pierre-Luc, Guillaume-Alexandre Bilodeau, and Robert Bergevin. “A Self-Adjusting Approach to Change Detection Based on Background Word Consensus.” In Applications of Computer Vision (WACV), 2015 IEEE Winter Conference on, pp. 990-997. IEEE, 2015.
  9. St-Charles, Pierre-Luc, Guillaume-Alexandre Bilodeau, and Robert Bergevin. “SuBSENSE: A Universal Change Detection Method With Local Adaptive Sensitivity.” Image Processing, IEEE Transactions on 24, no. 1 (2015): 359-373. [CrossRef]
  10. Zivkovic, Zoran. “Improved adaptive Gaussian mixture model for background subtraction.” In Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on, vol. 2, pp. 28-31. IEEE, 2004.
  11. Sebastian, Brutzer, Benjamin Höferlin, and Gunther Heidemann. “Evaluation of background subtraction techniques for video surveillance.” In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, pp. 1937-1944. IEEE, 2011.
  12. Parks, Donovan H., and Sidney S. Fels. “Evaluation of background subtraction algorithms with post-processing.” In Advanced Video and Signal Based Surveillance, 2008. AVSS’08. IEEE Fifth International Conference on, pp. 192-199. IEEE, 2008.
  13. Radke, Richard J., Srinivas Andra, Omar Al-Kofahi, and Badrinath Roysam. “Image change detection algorithms: a systematic survey.” Image Processing, IEEE Transactions on 14, no. 3 (2005): 294-307. [CrossRef]
  14. Hofmann, Martin, Philipp Tiefenbacher, and Gerhard Rigoll. “Background segmentation with feedback: The pixel-based adaptive segmenter.” In Computer Vision and Pattern Recognition Workshops (CVPRW), 2012 IEEE Computer Society Conference on, pp. 38-43. IEEE, 2012.
  15. Taycher, Leonid, Fisher John W. III, and Trevor Darrell. “Incorporating object tracking feedback into background maintenance framework.” In Application of Computer Vision, 2005. WACV/MOTIONS’05 Volume 1. Seventh IEEE Workshops on, vol. 2, pp. 120-125. IEEE, 2005. [CrossRef]
  16. Wang, Rui, Filiz Bunyak, Guna Seetharaman, and Kannappan Palaniappan. “Static and moving object detection using flux tensor with split Gaussian models.” In Computer Vision and Pattern Recognition Workshops (CVPRW), 2014 IEEE Conference on, pp. 420-424. IEEE, 2014.
  17. Hartigan, John A. Clustering algorithms. John Wiley & Sons, Inc., 1975.
  18. Cheng, Ming, Niloy J. Mitra, Xumin Huang, Philip HS Torr, and Song Hu. “Global contrast based salient region detection.” Pattern Analysis and Machine Intelligence, IEEE Transactions on 37, no. 3 (2015): 569-582. [CrossRef]
  19. Van Droogenbroeck, Marc, and Olivier Paquot. “Background subtraction: Experiments and improvements for ViBe.” In Computer Vision and Pattern Recognition Workshops (CVPRW), 2012 IEEE Computer Society Conference on, pp. 32-37. IEEE, 2012.
  20. changedetection website. http://changedetection.net/.

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.