Semi-automatic object-based video segmentation with labeling of color segments

Signal Processing: Image Communication

Volumn 18, Issue 1, 2003, Pages 51-65

  Patras, Ioannis ^a   Hendriks, Emile A ^b   Lagendijk, Reginald L ^b  

^a UNIVERSITY OF AMSTERDAM   (Netherlands)

^b DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

Author keywords

Image segmentation; Object based segmentation; Tracking; Video analysis

Indexed keywords

COLOR IMAGE PROCESSING; COMPUTER SIMULATION; IMAGE ANALYSIS; OPTIMIZATION; PROBABILITY; STATISTICAL METHODS;

OBJECT-BASED SEGMENTATION;

IMAGE SEGMENTATION;

EID: 0037210889     PISSN: 09235965     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0923-5965(02)00092-9     Document Type: Article

References (25)

1. Altunbasak Y., Eren P.E., Tekalp A.M. Region-based parametric motion segmentation using color information. Graphical Models Image Process. 60(1):January 1998;13-23.
2. S. Ayer, Sequential and competitive methods for estimation of multiple motions, Ph.D. Thesis, Ecole Polytechnique Federale de Lausanne, 1995.
3. Brown R.G., Hwang P.Y.C. Introduction to Random Signals and Applied Kalman Filtering. 3rd Edition:1996;Wiley, New York.
4. Castagno R., Ebrahimi T., Kunt M. Video segmentation based on multiple features for interactive multimedia applications. IEEE Trans. Circuits Systems Video Technol. 8(5):September 1998;562-571.
5. E. Chalom, Statistical image sequence segmentation using multidimensional attributes, Ph.D. Thesis, Massachusetts Institute of Technology, 1998.
6. Dempster A.P., Laird N.M., Rubin D.B. Maximum likelihood from incomplete data via the em algorithm. J. Roy. Stat. Soc., Ser. B. 1:1977;1-38.
7. A. Vetro (Ed.), MPEG-7: Applications document, Technical Report ISO/IEC JTC1/SC29/WG11/N3934, MPEG, January 2001. Pisa. http://www.cselt.it/mpeg/public/mpeg-7_applications.zip.
8. Gu C., Lee M.-C. Semiautomatic segmentation and tracking of semantic video objects. IEEE Trans. Circuits Systems Video Technol. 8(5):September 1998;572-584.
9. C. Gu, Multivalued morphology and segmentation-based coding, Ph.D. Thesis, Ecole Polytechnique Federale de Lausanne, 1995.
10. F. Marques, J. Llach, Tracking of generic objects for video object generation, in: Proceedings of the IEEE International Conference on Image Processing, Chicago, USA, 1998.
11. Nguyen H.T., Worring M., Boomgaard R.V.D., Smeulders A.W.M. Tracking non-parametrized object contours in video. IEEE Trans. Image Process. 11(9):September 2002.
12. N.E. O'Connor, N. Brady, S. Marlow, Supervised image segmentation using em-based estimation of mixture density parameters, in: Workshop on Image Analysis for Multimedia Interactive Services, June 1997, pp. 27-32.
13. N. Oliver, A. Pentland, F. Berard, Lafter: lips and face real time tracker with facial expression recognition, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Puerto Rico, June 1997, pp. 123-129.
14. Papas T.N. An adaptive clustering algorithm for image segmentation. IEEE Trans. Signal Process. 40(4):April 1992;901-914.
15. N. Paragios, R. Deriche, A pde-based level set approach for detection and tracking of moving objects, in: Proceedings of the IEEE International Conference on Computer Vision, Bombay, India, January 1998, pp. 1139-1145.
16. Paragios N., Tziritas G. Adaptive detection and localization of moving objects in image sequences. Signal Processing: Image Communication. 14(4):February 1999;278-296.
17. I. Patras, E.A. Hendriks, R.L. Lagendijk, A semi-automatic method for segmentation of image sequences with local region-based classification, in: International Conference on Signal and Image Processing, Las Vegas, USA, November 2000.
18. Patras I., Hendriks E.A., Lagendijk R.L. Video segmentation by map labeling of watershed segments. IEEE Trans. Pattern Anal. Machine Intell. 22(3):March 2001;326-332.
19. Shafarekno L., Petrou M., Kittler J. Automatic watershed segmentation of randomly textured color images. IEEE Trans. Image Process. 6(11):November 1997;1530-1544.
20. P. Shalembier, J. Serra, Morphological multiscale image segmentation, in: Proceedings of the SPIE Visual Communications and Image Processing, Vol. 1818, Boston, MA, November 1992, pp. 620-631.
21. H. Tao, H.S. Sawhney, R. Kumar, Dynamic layer representation and its applications to tracking, in: Proceedings of the IEEE Conference Computer Vision and Pattern Recognition, Hilton Head, June 2000.
22. Theodoridis S., Koutroumbas K. Pattern Recognition. 1999;Academic Press, New York.
23. F. Zanoguera, B. Marcotegui, F. Meyer, A toolbox for interactive segmentation based on nested partitions, in: Proceedings of the IEEE International Conference Image Processing, 1999.
24. Zhang J., Modestino J.W., Langan D.A. Maximum-likelihood parameter estimation for unsupervised stochastic model-based image segmentation. IEEE Trans. Image Process. 3(4):July 1994;404-419.
25. Zhong D., Chang S.-F. An integrated approach for content-based object segmentation and retrieval. IEEE Trans. Circuits Systems Video Technol. 9(8):December 1999;1259-1268.