Object boundary detection in images using a semantic ontology

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn 2006, Issue , 2006, Pages 111-

  Hoogs, Anthony ^a   Collins, Roderic ^a  

^a GE GLOBAL RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE SEGMENTATION; PROBLEM SOLVING; SEMANTICS;

BOUNDARY DETECTION; IMAGE SEGMENT;

IMAGE PROCESSING;

EID: 33845545436     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2006.145     Document Type: Conference Paper

References (17)

1. K. Barnard, P. Duygulu, N. de Freitas, D. Forsyth, D. Blei, and M. I. Jordan. Matching words and pictures. Journal of Machine Learning and Research, 3:1107-1135, 2003.
2. A. Budanitsky and G. HirstWu. Semantic distance in WordNet: An experimental, application-oriented evaluation of five measures. In Proceedings of the NAACL Workshop on WordNet and other Lexical Resources, Morgan Kaufmann, 2001.
3. Y. Chen and J. Wang. A region-based fuzzy feature matching approach to content-based image retrieval. IEEE Trans. on Pattern Analysis and Machine Intelligence, 24(9):1252-1267, Sept. 2002.
4. D. Comaniciu and P. Meer. Mean shift: a robust approach toward feature space analysis. IEEE Trans, on Pattern Analysis and Machine Intelligence, 24(5):603-619, May 2002.
5. L. Fei-Fei, R. Fergus, and P. Perona. Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories. In Proceedings of the Workshop on Generative-Model Based Vision. IEEE, 2004.
6. C. Fellbaum, editor. WordNet: An Electronic Lexical Database. MIT Press, Cambridge, MA, 1998.
7. X. Feng, C. Williams, and S. Felderhof. Combining belief networks and neural networks for scene segmentation. IEEE Trans. on Pattern Analysis and Machine Intelligence, 24(4):467-483, Apr. 2002.
8. M. Fritz, B. Leibe, B. Caputo, and B. Schiele. Integrating representative and discriminant models for object category detection. In Proc. IEEE International Conference on Computer Vision, 2005.
9. A. Hoogs, J. Rittscher, G. Stein, and J. Schmiederer. Video content annotation using visual analysis and large semantic knowledgebase. In Proc. IEEE Conf. on Computer Vision and Pattern Recognition. IEEE, 2003.
10. S. Konishi and A. Yuille. Stastistical cues for domain specific image segmentation with performance analysis. In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, 2000.
11. S. Kumar and M. Hebert. A hierarchical field framework for unified context-based classification. In Proc. IEEE International Conference on Computer Vision, 2005.
12. D. Lenat and R. Guha. Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project. Addison-Wesley, Reading, MA, 1990.
13. T. Leung and J. Malik. Recognizing surfaces using three-dimensional textures. In Proc. IEEE International Conference on Computer Vision. IEEE, 1999.
14. J. Malik, S. Belongie, T. Leung, and J. Shi. Contour and texture analysis for image segmentation. Int. J. Computer Vision, 43(1):7-27, June 2001.
15. D. Martin, C. Fowlkes, and J. Malik. Learning to detect natural image boundaries using brightness and texture. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2003.
16. D. Martin and J. Malik. The ucb segmentation benchmark database. URL: www.cs.berkeley.edu/projects/vision/grouping/segbench/.
17. S. Yu. Segmentation induced by scale invariance. In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, 2005.