Moving objects detection and segmentation based on background subtraction and image over-segmentation

Journal of Software

Volumn 6, Issue 7, 2011, Pages 1361-1367

  Zhu, Yun Fang ^a  

^a ZHEJIANG GONGSHANG UNIVERSITY   (China)

Author keywords

Background subtraction; Color clustering; Mixture of gaussians; Moving objection detection

Indexed keywords

BACKGROUND MODEL; BACKGROUND SUBTRACTION; COLOR CLUSTERING; COLOR INFORMATION; CONNECTED COMPONENT LABELING; MIXTURE OF GAUSSIANS; MOVING OBJECTION DETECTION; MOVING OBJECTS; MOVING OBJECTS DETECTION; OVER SEGMENTATION; POST PROCESS; SEGMENTATION RESULTS; SHADOW SUPPRESSION; SMALL AREA; VISION-BASED APPLICATIONS;

COLOR; MIXTURES;

IMAGE SEGMENTATION;

EID: 79960774449     PISSN: 1796217X     EISSN: None     Source Type: Journal    
DOI: 10.4304/jsw.6.7.1361-1367     Document Type: Article

References (21)

1. C Niu, Y Liu, Moving object segmentation in the H. 264 compressed domain, Lecture Notes in Computer Science,vol 5995,2010:645-654.
2. W Wang, J Yang, W Gao,Modeling Background and Segmenting Moving Objects from Compressed Video, IEEE Transactions on Circuits and Systems for video technology, Vol. 18, No. 5, 2008:670-681.
3. Jens Klappstein, Tobi Vaudrey, Clemens Rabe, Andreas Wedel et al,Moving Object Segmentation Using Optical Flow and Depth Information,Lecture Notes in Computer Science, Vol 5414,2009:611-623
4. Piccardi M. Background subtraction techniques: a review. IEEE International Conference on Systems, Man and Cybernetics, 2004, vol.4: 3099-3104.
5. Stauffer C, Grimson W.E.L. Adaptive background mixture models for real-time tracking. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Ft. Collins, 1999: 246-252.
6. Horprasert T, Harwood D, Davis L.S, A Statistical Approach for Real-time Robust Background Subtraction and Shadow Detection. Proceedings of IEEE ICCV' 99 Frame-Rate Workshop, 1999, pp.1-19.
7. [7] KaewTraKulPong P., Bowden R. An Improved Adaptive Background Mixture Model for Realtime Tracking with Shadow Detection. In Proc. 2nd European Workshop on Advanced Video Based Surveillance Systems, Sept 2001, Pages:1-5.
8. Elgammal A., Harwood D., Davis L. Non-parametric Model for Background Subtraction. in Proc. 6th Eur. Conf. Computer Vision, vol. 2, 2000, pp. 751-767.
9. Dar-Shyang Lee. Effective Gaussian mixture learning for video background subtraction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(5):827-832.
10. KaewTraKulPong P., Bowden R. An improved adaptive background mixture model for real-time tracking with shadow detection. in Proceedings of the 2nd European Workshop on Advanced Video-Based Surveillance Systems, Sept. 2001.
11. http://www.cvg.rdg.ac.uk/PETS2009/a.html
12. Intel Open Source Computer Vision Library. URL http://www.intel.com/research/mrl/research/opencv/.
13. Gao X., Boult T., Coetzee F., Ramesh V. Error analysis of background adaption. in Proceedings IEEE conference on computer vision and pattern recognition, 2000, vol.1, pp. 503-510.
14. Power P. W., Schoonees J. A. Understanding background mixture models for foreground segmentation. in Proceedings Image and Vision Computing, 2002, pp:267-271.
15. [15] Lee D.S., Hull J., Erol B. A Bayesian framework for gaussian mixture background modeling. in Proceedings of IEEE International Confererence on Image Processing, 2003, pages:973-976
16. Mittal A., Huttenlocher D. Scene modeling for wide area surveillancd and image synthesis. in Proceedings IEEE conference on computer vision and pattern recognition, 2, pp. 160-167, (Hilton Head Isand, SC), June 2000.
17. Cucchiara R., Grana C., Piccardi M., Prati A., Sirotti S. Improving shadow suppression in moving object detection with HSV color information. Intelligent Transportation Systems, 2001. Proceedings. 2001 IEEE, 25-29 Aug. 2001 Page(s):334-339.
18. Lucchese L., Mitra S. K. Color image segmentation: A state-of-the-art survey. in Proc. Indian National Science Academy(INSA-A), vol. 67, A, New Delhi, India, Mar. 2001, pp. 207-221.
19. C. Lawrence Zitnick, Sing Bing Kang, Matthew Uyttendaele, Simon Winder, Richard Szeliski. Highquality video view interpolation using a layered representation. Proceedings of ACM SIGGRAPH 2004, Pages: 600-608.
20. C. Lawrence Zitnick, Sing Bing Kang. Stereo for Image-Based Rendering using Image Over-Segmentation. International Journal of Computer Vision, 2007, 75(1):49-65.
21. Michael Kass, Andrew Witkin, Demetri Terzopoulos. Snakes: Active contour models. International Journal of Computer Vision. 1988, 1(4): 321-331.