Sketch recognition in interspersed drawings using time-based graphical models

Computers and Graphics (Pergamon)

Volumn 32, Issue 5, 2008, Pages 500-510

  Sezgin, T M ^a   Davis, R ^b  

^a KOÇ UNIVERSITY   (Turkey)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Dynamic Bayesian networks; Temporal sketch recognition; User interfaces

Indexed keywords

MICROCOMPUTERS; USER INTERFACES;

DYNAMIC BAYESIAN NETWORKS; ENABLING TECHNOLOGIES; PEN-BASED COMPUTERS; PEN-BASED INTERFACES; SKETCH RECOGNITION; STATISTICAL FRAMEWORK; TEMPORAL INFORMATION; TEMPORAL PATTERN;

BAYESIAN NETWORKS;

EID: 51449091783     PISSN: 00978493     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cag.2008.05.008     Document Type: Article

References (36)

1. Tversky BG. What does drawing reveal about thinking? Invited talk at first international workshop on visual and spatial reasoning in design, Cambridge, MA; 1999.
2. van Sommers P. Drawing and cognition descriptive and experimental studies of graphic production processes (1984), Cambridge University Press
3. Simhon S, Dudek G. "Sketch Interpretation and Refinement Using Statistical Models," Proc. 15th Eurographics Symp. Rendering (EGSR 04), Eurographics Assoc., 2004, pp. 23-32.
4. Anderson D., Bailey C., and Skubic M. Hidden markov model symbol recognition for sketch-based interfaces. AAAI fall symposium series making pen-based interaction intelligent and natural (2004)
5. Sezgin TM, Davis R. HMM-based efficient sketch recognition. In: Proceedings of the 10th international conference on intelligent user interfaces, San Diego, CA, USA; 2005, p. 281-3.
6. Sezgin T.M., and Davis R. Sketch interpretation using multiscale models of temporal patterns. IEEE Computer Graphics and Applications 27 1 (2007) 28-37
7. Alvarado C, Lazzereschi M. Properties of real world digital logic diagrams. Submitted to first international workshop on pen-based learning technologies; 2007.
8. Bilmes J.A. Dynamic Bayesian multinets. Proceedings of the 16th conference on uncertainty in artificial intelligence (2000)
9. Geiger D., and Heckerman D. Knowledge representation and inference in similarity networks and Bayesian multinets. Artificial Intelligence 82 (1996) 4574
10. Boutilier C, Friedman N, Goldszmidt M, Koller D. Context-specific independence in Bayesian networks. In Proc. 12'th Conf. Uncertainty in Artificial Intelligence, pp. 115-123. 1996.
11. Murphy K. Dynamic Bayesian networks. In: Jordan M. (Ed). Probabilistic graphical models (2002)
12. Bilmes J, Zweig G. The graphical models toolkit: an open source software system for speech and time-series processing. In: IEEE ICASSP, Orlando, FL; 2002.
13. Sezgin T.M., Stahovich T., and Davis R. Sketch based interfaces: early processing for sketch understanding. Proceedings of PUI (2001)
14. Murphy K. Dynamic Bayesian networks: representation, inference and learning. PhD thesis, UC Berkeley; 2002.
15. Murphy K, Mian S. Modelling gene expression data using dynamic Bayesian networks. Technical Report, Computer Science Division, University of California, Berkeley, CA; 1999.
16. Koller D., and Fratkina R. Using learning for approximation in stochastic processes. Proceedings of the 15th international conference on machine learning (1998)
17. Sezgin TM. Online sketch recognition from a dynamic perspective. PhD thesis, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology; June 2006.
18. Mahoney J.V., and Fromherz M.P.J. Three main concerns in sketch recognition and an approach to addressing them. AAAI spring symposium: sketch understanding (2002)
19. Rubine D. Specifying gestures by example. Computer Graphics 25 4 (1991) 329-337
20. Apte A, Vo V, Kimura TD. Recognizing multistroke geometric shapes: an experimental evaluation. In: Proceedings of the sixth annual ACM symposium on user interface software and technology, Atlanta, Georgia, United States; 1993, p. 121-8.
21. Sun Z, Liu W, Peng B, Zhang B, Jianyong S. User adaptation for online sketchy shape recognition. In: GREC 2003, Barcelona, Spain, July 30-31; 2003 (Revised Selected Papers. Graphics recognition: recent advances and perspectives, In: Fifth international workshop. Lecture notes in computer science, vol. 3088, Springer, Heidelberg: Berlin; 2004. p. 305. ISSN: 0302-9743.)
22. Watanabe T., Sugawara K., and Sugihara H. A new pattern representation scheme using data compression. IEEE Transactions on Pattern Analysis and Machine Intelligence 24 5 (2002) 579-590
23. Hse H., and Newton A.R. Recognition and beautification of multi-stroke symbols. AAAI fall symposium series 2004 (2004)
24. Kara L.B., and Stahovich T.F. An image-based trainable symbol recognizer for sketch-based interfaces. AAAI fall symposium series 2004 (2004)
25. Sharon D., and van de Panne M. Constellation models for sketch recognition. Eurographics workshop on sketch based interfaces and modeling (2006)
26. Alvarado C., and Davis R. Sketchread: a multi-domain sketch recognition engine. Proceedings of UIST (2004)
27. Shilman M, Pasula H, Russel S, Newton R. Statistical visual language models for ink parsing. In: AAAI spring symposium: sketch understanding, Stanford CA, March 25-27, 2002.
28. Hammond T., and Davis R. Interactive learning of structural shape descriptions from automatically generated near-miss examples. Intelligent user interfaces (IUI) (2006)
29. Veselova O. Perceptually based learning of shape descriptions. Masters Thesis, Cambridge: MIT; 2003.
30. Krishnapuram B. Bishop C. Szummer M. Generative models and Bayesian model comparison for shape recognition. In: IWFHR '04, Japan; 2004.
31. Mahoney JV, Fromherz MPJ. Handling ambiguity in constraint-based recognition of stick figure sketches. In: SPIE document recognition and retrieval IX conference, San Jose, CA; January 2002.
32. Cowans P.J., and Szummer M. A graphical model for simultaneous partitioning and labeling. AI & Statistics (January 2005)
33. Gennari L., Kara L.B., and Stahovich T.F. Combining geometry and domain knowledge to interpret hand-drawn diagrams. AAAI fall symposium series, making pen-based interaction intelligent and natural (2004)
34. Shilman M, Viola P. Spatial Recognition and Grouping of Text and Graphics. Eurographics Workshop on Sketch-Based Interfaces and Modeling (Eurographics SBIM) 2004.
35. Cohen P., Johnston M., McGee D., Oviatt S., Pittman J., Smith I., et al. Quickset: multimodal interaction for distributed applications. ACM MM 1997 (1997)
36. Zweig G., and Russell S. Probabilistic Modeling with Bayesian Networks for Automatic Speech Recognition. Australian Journal of Intelligent Information Processing Systems 5 4 (1999) 253-260