Specifying gestures by example
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Interactive beautification: a technique for rapid geometric design
Proceedings of the 10th annual ACM symposium on User interface software and technology
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
A Simple Approach to Recognise Geometric Shapes Interactively
GREC '99 Selected Papers from the Third International Workshop on Graphics Recognition, Recent Advances
Naturally conveyed explanations of device behavior
Proceedings of the 2001 workshop on Perceptive user interfaces
Tahuti: a geometrical sketch recognition system for UML class diagrams
ACM SIGGRAPH 2006 Courses
Free-sketch recognition: putting the chi in sketching
CHI '08 Extended Abstracts on Human Factors in Computing Systems
PaleoSketch: accurate primitive sketch recognition and beautification
Proceedings of the 13th international conference on Intelligent user interfaces
Ink features for diagram recognition
SBIM '07 Proceedings of the 4th Eurographics workshop on Sketch-based interfaces and modeling
Lineogrammer: creating diagrams by drawing
Proceedings of the 21st annual ACM symposium on User interface software and technology
Sort, merge, repeat: an algorithm for effectively finding corners in hand-sketched strokes
Proceedings of the 6th Eurographics Symposium on Sketch-Based Interfaces and Modeling
SketchML a representation language for novel sketch recognition approach
Proceedings of the 2nd International Conference on PErvasive Technologies Related to Assistive Environments
Automated freehand sketch segmentation using radial basis functions
Computer-Aided Design
Multimodal interaction with an autonomous forklift
Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction
The power of automatic feature selection: Rubine on steroids
Proceedings of the Seventh Sketch-Based Interfaces and Modeling Symposium
Rata.SSR: data mining for pertinent stroke recognizers
Proceedings of the Seventh Sketch-Based Interfaces and Modeling Symposium
Technical Section: SpeedSeg: A technique for segmenting pen strokes using pen speed
Computers and Graphics
ClassySeg: a machine learning approach to automatic stroke segmentation
Proceedings of the Eighth Eurographics Symposium on Sketch-Based Interfaces and Modeling
Combining corners from multiple segmenters
Proceedings of the Eighth Eurographics Symposium on Sketch-Based Interfaces and Modeling
Recognizing sketched multistroke primitives
ACM Transactions on Interactive Intelligent Systems (TiiS)
ShortStraw: a simple and effective corner finder for polylines
SBM'08 Proceedings of the Fifth Eurographics conference on Sketch-Based Interfaces and Modeling
A data collection tool for sketched diagrams
SBM'08 Proceedings of the Fifth Eurographics conference on Sketch-Based Interfaces and Modeling
Recognition of multi-touch drawn sketches
HCI'13 Proceedings of the 15th international conference on Human-Computer Interaction: interaction modalities and techniques - Volume Part IV
Technical Section: A machine learning approach to automatic stroke segmentation
Computers and Graphics
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Freehand sketching is a natural and powerful means of interpersonal communication. But to date, it still cannot be supported effectively by human-computer interface. In this paper, we describe a domain-independent system for sketch recognition. Our system allows users to draw sketches as naturally as how they do on paper, and it recognizes the drawing through imprecise stroke approximation which is implemented in a unified and incremental procedure. This method can handle smooth curves and hybrid shapes as gracefully as it does to polylines. With a feature-area verification mechanism and the intelligent adjustment in the post-process, the system can produce user-intended results. Moreover, the output is organized in a hierarchical structure which includes syntactic and semantic information as well as raw data. Our system mainly utilizes low-level geometric features and does not rely on any domain-specific knowledge. Therefore, it will serve as a general and solid foundation for future high-level applications.