Robust foreground extraction technique using Gaussian Family model and multiple thresholds

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4843 LNCS, Issue PART 1, 2007, Pages 758-768

  Kim, Hansung ^a   Sakamoto, Ryuuki ^a   Kitahara, Itaru ^a,b   Toriyama, Tomoji ^a   Kogure, Kiyoshi ^a  

^a ADVANCED TELECOMMUNICATIONS RESEARCH INSTITUTE INTERNATIONAL   (Japan)

^b UNIVERSITY OF TSUKUBA   (Japan)

Author keywords

Background subtraction; Foreground segmentation; Generalized Gaussian Family model; Silhouette extraction

Indexed keywords

ALGORITHMS; COLOR VISION; GAUSSIAN DISTRIBUTION; PIXELS;

COLOR VIDEO SEQUENCES; GAUSSIAN FAMILY MODEL; SILHOUETTE EXTRACTION;

FEATURE EXTRACTION;

EID: 38149078188     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-76386-4_72     Document Type: Conference Paper

References (24)

1. Gelasca, E.D., Ebrahimi, T., Karaman, M., Sikora, T.: A Framework for Evaluating Video Object Segmentation Algorithms. In: Proc. CVPR Workshop, pp. 198-198 (2006)
2. Piccardi, M.: Background Subtraction techniques: a review. In: Proc. IEEE. SMC, vol. 4, pp. 3099-3104 (2004)
3. Kumar, P., Sengupta, K., Ranganath, S.: Real time detection and recognition of human profiles using inexpensive desktop cameras. In: Proc. ICPR, pp. 1096-1099 (2000)
4. Jabri, S., Duric, Z., Rosenfeld, A., Wechsler, H.: Detection and location of people in video images using adaptive fusion of color and edge information. In: Proc. ICPR, pp. 627-630 (2000)
5. Horprasert, T., Harwood, D., Davis, L.S.: A robust background subtraction and shadow detection. In: Proc. ACCV (2000)
6. McKenna, S.J., Jabri, S., Duric, Z., Rosenfeld, A., Wechsler, H.: Tracking Groups of People. Computer Vision and Image Understanding 80(1), 42-56 (2000)
7. Wren, C., Azarbayejani, A., Darrell, T., Pentland, A.P.: Pfinder: Real-Time Tracking of the Human Body. IEEE Trans. PAMI 19(7), 780-785 (1997)
8. Stauffer, C., Grimson, W.E.L.: Adaptive background mixture models for real-time tracking. In: Proc. CVPR, pp. 246-252 (1999)
9. Lee, D.S., Hull, J.J., Erol, B.: A Bayesian framework for Gaussian mixture background modeling. In: Proc. ICIP, vol. 3, pp. 973-976 (2003)
10. Javed, O., Shafique, K., Shah, M.: A hierarchical approach to robust background subtraction using color and gradient information. In: Proc. IEEE Motion and Video Computing, pp. 22-27. IEEE Computer Society Press, Los Alamitos (2002)
11. Porikli, F., Tuzel, O.: Human body tracking by adaptive background models and mean-shift analysis. In: Proc. PETS-ICVS (2003)
12. Cristani, M., Bicego, M., Murino, V.: Integrated region- and pixel based approach to background modeling. In: Proc. IEEE MVC, pp. 3-8. IEEE Computer Society Press, Los Alamitos (2002)
13. Elgammal, A., Harwood, D., Davis, L.S.: Non-parametric model for background subtraction. In: Proc. ECCV, vol. 2, pp. 751-767 (2000)
14. Tuzel, O., Porikli, F., Meer, P.: A Bayesian Approach to Background Modeling. In: Proc. IEEE MVIV, vol. 3, pp. 58-63 (2005)
15. Han, B., Comaniciu, D., Davis, L.: Sequential kernel density approximation through mode propagation: applications to background modeling. In: Proc. ACCV (2004)
16. Mittal, A., Paragios, N.: Motion-based background subtraction using adaptive kernel density estimation. In: Proc. CVPR, pp. 302-309 (2004)
17. Kim, K., Chalidabhongse, T.H., Harwood, D., Davis, L.S.: Real-time foreground-background segmentation using codebook model. Real-Time Imaging 11, 172-185 (2005)
18. Wang, D., Feng, T., Shum, H., Ma, S.: Novel probability model for background maintenance and subtraction. In: Proc. ICVI (2002)
19. Stenger, B., Ramesh, V., Paragios, N., Coetzee, F., Buhmann, J.: Topology free hidden Markov models: Application to background modeling. In: Proc. ICCV, pp. 294-301 (2001)
20. Zhong, J., Sclaroff, S.: Segmenting foreground objects from a dynamic textured background via a robust Kalman filter. In: Proc. ICCV, pp. 44-50 (2003)
21. Monnet, A., Mittal, A., Paragios, N., Ramesh, V.: Background modeling and subtraction of dynamic scenes. In: Proc. ICCV, pp. 1305-1312 (2003)
22. Lee, J.Y., Nandi, A.K.: Maximum Likelihood Parameter Estimation of the Asymmetric Generalized Gaussian Family of Distribution. In: Proc. SPW-HOS (1999)
23. Kotz, S., Kozubowski, T.J., Podgorski, K.: Maximum likelihood estimation of asymmetric Laplace parameters. Ann. Inst. Statist. Math. 54, 816-826 (2002)
24. Shapiro, L.G., Stockman, G.C.: Computer Vision. Prentice Hall, New Jersey (2001)