A new approach to early sketch processing

AAAI Fall Symposium - Technical Report

Volumn FS-04-06, Issue , 2004, Pages 29-34

  Cates, Sonya ^a   Davis, Randall ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GRAPHICAL MODEL; SKETCH PROCESSING;

ARTIFICIAL INTELLIGENCE; FEATURE EXTRACTION; PROBLEM SOLVING;

PATTERN RECOGNITION;

EID: 32844462456     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. Alvarado, C. 2004. Multi-Domain Sketch Understanding. Ph.D. Dissertation, Massachusetts Institute of Technology.
2. Coughlan, J. M., and Ferreira, S. J. 2002. Finding deformable shapes using loopy belief propagation. In Proceedings of European Conference on Computer Vision.
3. Gross, M. D., and Do, E. Y.-L. 2000. Drawing on the back of an envelope: a framework for interacting with application programs by freehand drawing. Computers & Graphics 24.
4. Hse, H.; Shilman, M.; and Newton, A. R. 2004. Robust sketched symbol fragmentation using templates. In Proceedings of Intelligent User Interfaces.
5. Murphy, K. P.; Weiss, Y.; and Jordan, M. I. 1999. Loopy belief propagation for approximate inference: An empirical study. In Proceedings of Uncertainty in Artificial Intelligence.
6. Roth, D., and Yih, W. 2002. Probabilistic reasoning for entity & relation recognitions. In Proceedings of International Conference on Computational Linguistics.
7. Saund, E.; Mahoney, J.; Fleet, D.; Larner, D.; and Lank, E. 2002. Perceptual organization as a foundation for intelligent sketch editing. In AAAI Spring Symposium on Sketch Understanding.
8. Yedidia, J. S.; Freeman, W. T.; and Weiss, Y 2000. Generalized belief propogation. Technical Report TR-2000-26, Mitsubishi Electric Research Laboratory.
9. Yedidia, J. S.; Freeman, W. T.; and Weiss, Y. 2002. Understanding belief propogation and its generalizations. Technical Report TR-2001-22, Mitsubishi Electric Research Laboratory.
10. Zhang, D.-Q., and Chang, S.-F. 2004. Learning to detect scene text using a higher-order mrf with belief propagation. In IEEE Workshop on Learning in Computer Vision and Pattern Recognitions.