Recursive error-compensated dynamic eigenbackground learning and adaptive background subtraction in video

Optical Engineering

Volumn 47, Issue 5, 2008, Pages

  Xu, Zhifei ^a   Gu, Irene Yu Hua ^b   Shi, Pengfei ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b CHALMERS UNIVERSITY OF TECHNOLOGY   (Sweden)

Author keywords

background modeling; background subtraction; eigenbackground; recursive error compensation; video surveillance

Indexed keywords

BACKGROUND MODELING; BACKGROUND SUBTRACTION; EIGENBACKGROUND; RECURSIVE ERROR COMPENSATION; VIDEO SURVEILLANCE;

APPROXIMATION ALGORITHMS; COMPUTER APPLICATIONS; COMPUTER VISION; ERROR COMPENSATION; ERROR DETECTION;

FACE RECOGNITION;

EID: 78651568454     PISSN: 00913286     EISSN: 15602303     Source Type: Journal    
DOI: 10.1117/1.2919787     Document Type: Article

References (13)

1. C. R., Wren, A., Azarbayejani, T., Darrell, and A. P., Pentland, " Pfinder: real-time tracking of the human body, ", IEEE Trans. Pattern Anal. Mach. Intell., 19 (7), 780-785 (1997). ipa ITPIDJ 0162-8828 10.1109/34.598236 (Pubitemid 127762271)
2. C., Stauffer and W. E. L., Grimson, " Learning patterns of activity using real-time tracking, ", IEEE Trans. Pattern Anal. Mach. Intell., 22 (8), 747-757 (2000). ipa ITPIDJ 0162-8828 10.1109/34.868677
3. D.-S., Lee, " Effective Gaussian mixture learning for video background subtraction, ", IEEE Trans. Pattern Anal. Mach. Intell., 27 (5), 827-832 (2005). ipa ITPIDJ 0162-8828 10.1109/TPAMI.2005.102 (Pubitemid 40608416)
4. Z., Zivkovic and F. v. d., Heijden, " Efficient adaptive density estimation per image pixel for the task of background subtraction, ", Pattern Recogn. Lett., 27 (7), 773-780 (2006). prj PRLEDG 0167-8655 (Pubitemid 43374860)
5. Z., Zivkovic and F. v. d., Heijden, " Recursive unsupervised learning of finite mixture models, ", IEEE Trans. Pattern Anal. Mach. Intell., 26 (5), 651-656 (2004). ipa ITPIDJ 0162-8828
6. A., Elgammal, R., Duraiswami, D., Harwood, and L. S., Davis, " Background and foreground modeling using nonparametric kernel density estimation for visual surveillance, ", Proc. IEEE, 90 (7), 1151-1163 (2002). iee IEEPAD 0018-9219 10.1109/JPROC.2002.801448 (Pubitemid 43773332)
7. H., Wang and D., Suter, " A consensus-based method for tracking: modeling background scenario and foreground appearance, ", Pattern Recogn., 40 (3), 1091-1105 (2007). ptm PTNRA8 0031-3203 (Pubitemid 44667747)
8. K., Kim, T. H., Chalidabhongse, D., Harwood, and L. S., Davis, " Real-time foreground-background segmentation using codebook model, ", Real-Time Imag., 11 (3), 172-185 (2005). rti REIMFQ 1077-2014 (Pubitemid 40929458)
9. K., Toyama, J., Krumm, B., Brumitt, and B., Meyers, " Wallflower: principles and practice of background maintenance, " in, Proc. IEEE Conf. on Computer Vision, Vol. 1, pp. 255-261 (1999). (Pubitemid 32080048)
10. N. M., Oliver, B., Rosario, and A. P., Pentland, " A Bayesian computer vision System for modeling human interactions, ", IEEE Trans. Pattern Anal. Mach. Intell., 22 (8), 831-843 (2000). ipa ITPIDJ 0162-8828
11. J.-S., Park, Y. H., Oh, S. C., Ahn, and S.-W., Lee, " Glasses removal from facial image using recursive error compensation, ", IEEE Trans. Pattern Anal. Mach. Intell., 27 (5), 805-811 (2005). ipa ITPIDJ 0162-8828 (Pubitemid 40608412)
12. Q.-Z., Wu, H.-Y., Cheng, and B.-S., Jeng, " Motion detection via change-point detection for cumulative histograms of ratio images, ", Pattern Recogn. Lett., 26 (5), 555-563 (2005). prj PRLEDG 0167-8655 (Pubitemid 40319619)
13. L., Li, W., Huang, Y.-H., Gu, and Q., Tian, " Statistical modeling of complex backgrounds for foreground object detection, ", IEEE Trans. Image Process., 13 (11), 1459-1472 (2004). iei IIPRE4 1057-7149 10.1109/TIP.2004.836169