Real-time video object segmentation algorithm based on change detection and background updating

International Journal of Innovative Computing, Information and Control

Volumn 5, Issue 7, 2009, Pages 1797-1810

  Chen, Tsong Yi ^a   Chen, Thou Ho ^a   Wang, Da Jinn ^a   Chiou, Yung Chuen ^a  

^a NATIONAL KAOHSIUNG UNIVERSITY OF APPLIED SCIENCES   (Taiwan)

Author keywords

Background updating; Change detection; Video object segmentation

Indexed keywords

BACKGROUND SUBTRACTION; BACKGROUND UPDATING; BASIC IDEA; BOUNDARY REFINEMENTS; CHANGE DETECTION; CHANGE REGION; FRAME DIFFERENCE MASKS; OBJECTIVE EVALUATION; REAL TIME VIDEOS; SPATIAL ACCURACY; TEMPORAL INFORMATION; VIDEO OBJECT SEGMENTATION;

ALGORITHMS; MOTION COMPENSATION; SIGNAL DETECTION;

IMAGE SEGMENTATION;

EID: 67749117925     PISSN: 13494198     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (22)

1. T. Sikora, The MPEG-4 video standard verification model, IEEE Trans. on Circuits Syst. Video Technol., vol.7, pp.19-31, 1997.
2. P. Salembier and F. Marques, Region-based representation of image and video: Segmentation tool for multimedia services, IEEE Trans. on Circuits Syst. Video Technol., vol.9, pp.1147-1169, 1999.
3. M. Kim, J. G. Jeon, J. S. Kwak, M. H. Lee and C. Ahn, Moving object segmentation in video sequences by user interaction and automatic object tracking, Image and Vision Computing, vol.19, pp.245-260, 2001.
4. C. Toklu, A. M. Tekalp and A. T. Erdem, Semi-automatic video object segmentation in the presence of occlusion, IEEE Trans. on Circuits Syst. Video Technol., vol.10, no.4, pp.624-629, 2000.
5. T. Meier and K. N. Ngan, Video segmentation for content-based coding, IEEE Trans. on Circuits and System for Video Technol., vol.9, no.8, pp.1190-1203, 1999.
6. C. Kim and J. N. Hwang, Fast and automatic video object segmentation and tracking for contentbased application, IEEE Transaction on Circuits and System for Video Technology, vol.12, no.2, pp.122-129, 2002.
7. M. Kim, J. G. Choi, K. Daehee, H. Lee, M. H. Lee, C. Ahn and Y.-S. Ho, A VOP generation tool: automatic segmentation of moving object in image sequences based on spatio-temporal information, IEEE Trans. on Circuits Syst. Video Technol., vol.9, no.8, pp.1216-126, 2002.
8. R. Mech and M. Wollborn, A noise robust method for 2D shape estimation of moving object in video sequence considering a moving camera, Signal Processing, vol.66, pp.203-217, 1997.
9. S.-Y. Chien, Y.-W. Huang, B.-Y. Hsieh, S.-Y. Ma and L.-G. Chen, Fast video segmentation algorithm with shadow cancellation, global motion compensation, and adaptive threshold techniques, IEEE Trans. on Circuits and System for Video Technol., vol.6, no.5, pp.732-748, 2004.
10. S.-Y. Chien, S.-Y. Ma and L.-G. Chen, Efficient moving object segmentation algorithm using background registration technique, IEEE Trans. on Circuits Syst. Video Technol., vol.12, no.7, pp.577-586, 2002.
11. L. G. Shaprio and G. C. Stockman, Computer Vision, Prentice Hall, pp.149-152, 2001.
12. T. Aach, A. Kaup and R. Mester, Statisticl model-based change detection in moving video, Signal Processing, vol.31, pp.165-180, 1993.
13. J. Pan, C.-W. Lin, C. Gu and M.-T. Sun, A robust video object segmentation scheme with prestored background information, Proc. of the 2002 IEEE International Symposium on Circuits and Systems, vol.3, no.26-29, pp.803-806, 2002.
14. D.-S. Gao, J. Zhou and L.-P. Xin, A novel algorithm of adaptive background estimation, Proc. of the IEEE International Conference on Image Processing, vol.2, pp.395-398, 2001.
15. S. Huwer, Adaptive change detection for real-time surveillance applications, Proc. of the IEEE International Workshop on Visual Surveillance, pp.37-46, 2000.
16. C. Ridder, O. Munkelt and H. Kirchner, Adaptive background estimation and foreground detection using kalman-filtering, Proc. of the International Conference on Recent Advances in Mechatronics, pp.193-199, 1995.
17. A. Neri, S. Colonnese, G. Russo and P. Talone, Automatic moving object and background sepatation, Signal Processing, vol.66, pp.219-232, 1998.
18. R. C. Gonzalez and R. E. Wood, Digital Image Processing, 2Ed, New Jersey: Prentice Hall, 2002.
19. R. M. Haralick and L. G. Shapiro, Computer and Robot Vision, Reading, MA: Addison-Wesley, pp.28-48, 1992.
20. Z.-M. Lu, S.-Z. Li and H. Burkhardt, A content-based image retrieval scheme in JPEG compressed domain, International Journal of Innovative Computing, Information and Control, vol.2, no.4, pp.831-839, 2006.
21. Y. Aoki and T. Kato, A new segmentation in SAR image reconstruction, International Journal of Innovative Computing, Information and Control, vol.3, no.2, pp.235-245, 2007.
22. M. Wollborn and R. Mech, Refined procedure for objective evaluation of video object generation algorithm, Doc. ISO/IEC JTC1/SC29/WG11 M3448, 1998.