A perceptually-supported sketch editor
UIST '94 Proceedings of the 7th annual ACM symposium on User interface software and technology
Teddy: a sketching interface for 3D freeform design
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Handwritten Numeral String Recognition with Stroke Grouping
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Motion doodles: an interface for sketching character motion
ACM SIGGRAPH 2004 Papers
Recognition and Grouping of Handwritten Text in Diagrams and Equations
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Sketch-based modeling of parameterized objects
SIGGRAPH '05 ACM SIGGRAPH 2005 Sketches
Constellation models for sketch recognition
SBM'06 Proceedings of the Third Eurographics conference on Sketch-Based Interfaces and Modeling
SteerBug: an interactive framework for specifying and detecting steering behaviors
Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Sketch-based interfaces: exploiting spatio-temporal context for automatic stroke grouping
SG'10 Proceedings of the 10th international conference on Smart graphics
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The ability to recognize the strokes drawn by the user, is central to most sketch-based interfaces. However, very few solutions that rely on recognition are robust enough to make sketching a definitive alternative to traditional WIMP user interfaces. In this paper, we propose an approach based on classification that given an unconstrained sketch, can robustly assign a label to each stroke that comprises the sketch. A key contribution of our approach is a technique for grouping strokes that eliminates outliers and enhances the robustness of the classification. We also propose a set of features that capture important attributes of the shape and mutual relationship of strokes. These features are statistically well-behaved and enable robust classification with Support Vector Machines (SVM). We conclude by presenting a concrete implementation of these techniques in an interface for driving facial expressions.