Specifying gestures by example
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Machine Learning
Interactive sketching for the early stages of user interface design
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Interactive beautification: a technique for rapid geometric design
Proceedings of the 10th annual ACM symposium on User interface software and technology
An automatic beautifier for drawings and illustrations
SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
Visual similarity of pen gestures
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Fluid sketches: continuous recognition and morphing of simple hand-drawn shapes
UIST '00 Proceedings of the 13th annual ACM symposium on User interface software and technology
Constrained K-means Clustering with Background Knowledge
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Sketch based interfaces: early processing for sketch understanding
Proceedings of the 2001 workshop on Perceptive user interfaces
Sketched Symbol Recognition using Zernike Moments
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Hierarchical parsing and recognition of hand-sketched diagrams
Proceedings of the 17th annual ACM symposium on User interface software and technology
Sketch recognition with continuous feedback based on incremental intention extraction
Proceedings of the 10th international conference on Intelligent user interfaces
Beautifying sketching-based design tool content: issues and experiences
AUIC '05 Proceedings of the Sixth Australasian conference on User interface - Volume 40
An Incremental On-line Parsing Algorithm for Recognizing Sketching Diagrams
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01
Envisioning sketch recognition: a local feature based approach to recognizing informal sketches
Envisioning sketch recognition: a local feature based approach to recognizing informal sketches
PaleoSketch: accurate primitive sketch recognition and beautification
Proceedings of the 13th international conference on Intelligent user interfaces
Designing a sketch recognition front-end: user perception of interface elements
SBIM '07 Proceedings of the 4th Eurographics workshop on Sketch-based interfaces and modeling
Sketch recognition in interspersed drawings using time-based graphical models
Computers and Graphics
Iconic and multi-stroke gesture recognition
Pattern Recognition
Automatically transforming symbolic shape descriptions for use in sketch recognition
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Resolving ambiguities to create a natural computer-based sketching environment
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
LADDER, a sketching language for user interface developers
Computers and Graphics
Recognition and beautification of multi-stroke symbols in digital ink
Computers and Graphics
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
A visual approach to sketched symbol recognition
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
A model-based recognition engine for sketched diagrams
Journal of Visual Languages and Computing
Feature extraction and classifier combination for image-based sketch recognition
Proceedings of the Seventh Sketch-Based Interfaces and Modeling Symposium
Sketch recognition by fusion of temporal and image-based features
Pattern Recognition
Sketch interpretation and refinement using statistical models
EGSR'04 Proceedings of the Fifteenth Eurographics conference on Rendering Techniques
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Sketching is a natural mode of communication that can be used to support communication among humans. Recently there has been a growing interest in sketch recognition technologies for facilitating human-computer interaction in a variety of settings, including design, art, and teaching. Automatic sketch recognition is a challenging problem due to the variability in hand drawings, the variation in the order of strokes, and the similarity of symbol classes. In this paper, we focus on a more difficult task, namely the task of classifying sketched symbols before they are fully completed. There are two main challenges in recognizing partially drawn symbols. The first is deciding when a partial drawing contains sufficient information for recognizing it unambiguously among other visually similar classes in the domain. The second challenge is classifying the partial drawings correctly with this partial information. We describe a sketch auto-completion framework that addresses these challenges by learning visual appearances of partial drawings through semi-supervised clustering, followed by a supervised classification step that determines object classes. Our evaluation results show that, despite the inherent ambiguity in classifying partially drawn symbols, we achieve promising auto-completion accuracies for partial drawings. Furthermore, our results for full symbols match/surpass existing methods on full object recognition accuracies reported in the literature. Finally, our design allows real-time symbol classification, making our system applicable in real world applications.