Intensity range based background subtraction for effective object detection

IEEE Signal Processing Letters

Volumn 20, Issue 8, 2013, Pages 759-762

  Hati, Kalyan Kumar ^a   Sa, Pankaj Kumar ^a   Majhi, Banshidhar ^a  

^a NATIONAL INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Background modeling; background subtraction; video segmentation; video surveillance

Indexed keywords

BACKGROUND MODELING; BACKGROUND SUBTRACTION; COMPARATIVE ANALYSIS; ILLUMINATION VARIATION; QUANTITATIVE MEASURES; REAL-TIME SURVEILLANCE; VIDEO SEGMENTATION; VIDEO SURVEILLANCE;

ALGORITHMS; IMAGE SEGMENTATION; OBJECT RECOGNITION;

SECURITY SYSTEMS;

EID: 84879223285     PISSN: 10709908     EISSN: None     Source Type: Journal    
DOI: 10.1109/LSP.2013.2263800     Document Type: Article

References (14)

1. A. Yilmaz, O. Javed, and M. Shah, "Object tracking: A survey," ACM Comput. Surv., vol. 38, Dec. 2006.
2. C.Wren, A. Azarbayejani, T. Darrell, and A. Pentland, "Pfinder: Realtime tracking of the human body," IEEE Trans. Patt. Anal. Mach. Intell., vol. 19, no. 7, pp. 780-785, Jul. 1997. (Pubitemid 127762271)
3. C. Stauffer and W. Grimson, "Adaptive background mixture models for real-time tracking," in IEEE Comput. Soc. Conf. CVPR, 1999, pp. 246-252.
4. I. Haritaoglu, D. Harwood, and L. Davis, "W4: Real-time surveillance of people and their activities," IEEE Trans. Patt. Anal. Mach. Intell., vol. 22, no. 8, pp. 809-830, Aug. 2000.
5. J. Jacques, C. Jung, and S. Musse, "Background subtraction and shadow detection in grayscale video sequences," in Eighteenth Brazilian Symp. Computer Graphics and Image Processing, Oct. 2005, pp. 189-196.
6. J.McHugh, J. Konrad,V. Saligrama, and P. Jodoin, "Foreground- adaptive background subtraction," IEEE Signal Process.Letters, vol. 16, no. 5, pp. 390-393, May 2009.
7. O. Barnich and M. Van Droogenbroeck, "ViBe: A universal background subtraction algorithm for video sequences," IEEE Trans. Image Process., vol. 20, no. 6, pp. 1709-1724, Jun. 2011.
8. W. Kim and C. Kim, "Background subtraction for dynamic texture scenes using fuzzy color histograms," IEEE Signal Process. Lett., vol. 19, no. 3, pp. 127-130, Mar. 2012.
9. V. Reddy, C. Sanderson, and B. Lovell, "Improved foreground detection via block-based classifier cascade with probabilistic decision integration," IEEE Trans. Circuits Syst. Video Technol., vol. 23, no. 1, pp. 83-93, Jan. 2013.
10. E. Salvador, A. Cavallaro, and T. Ebrahimi, "Cast shadow segmentation using invariant color features," Comput. Vis. Image Understand., vol. 95, no. 2, pp. 238-259, 2004.
11. J. Choi, Y. Yoo, and J. Choi, "Adaptive shadow estimator for removing shadow of moving object," Comput. Vis. Image Understand., vol. 114, no. 9, pp. 1017-1029, 2010.
12. Z. Liu, K. Huang, and T. Tan, "Cast shadow removal in a hierarchical manner using MRF," IEEE Trans. Circuits Syst. Video Technol., vol. 22, no. 1, pp. 56-66, Jan. 2012.
13. L. Li,W.Huang, I.Y.H.Gu, andQ. Tian, "Foreground object detection from videos containing complex background," in Proc. Eleventh ACM Int. Conf. Multimedia, Nov. 2003, pp. 2-10.
14. Z. Zivkovic, "Improved adaptive Gausian mixture model for background subtraction," in Proc. IEEE Int. Conf Pattern Recognition,Aug. 2004, pp. 28-31.