Perceptually-supported image editing of text and graphics
Proceedings of the 16th annual ACM symposium on User interface software and technology
Stylus input and editing without prior selection of mode
Proceedings of the 16th annual ACM symposium on User interface software and technology
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
SketchREAD: a multi-domain sketch recognition engine
Proceedings of the 17th annual ACM symposium on User interface software and technology
Videotater: an approach for pen-based digital video segmentation and tagging
UIST '06 Proceedings of the 19th annual ACM symposium on User interface software and technology
Sloppy selection: Providing an accurate interpretation of imprecise selection gestures
Computers and Graphics
Combining geometry and domain knowledge to interpret hand-drawn diagrams
Computers and Graphics
Automatic evaluation of sketch recognizers
Proceedings of the 6th Eurographics Symposium on Sketch-Based Interfaces and Modeling
Proceedings of the 6th Eurographics Symposium on Sketch-Based Interfaces and Modeling
Sketch-based instancing of parameterized 3D models
Edutainment'10 Proceedings of the Entertainment for education, and 5th international conference on E-learning and games
ClassySeg: a machine learning approach to automatic stroke segmentation
Proceedings of the Eighth Eurographics Symposium on Sketch-Based Interfaces and Modeling
Automated labeling of ink stroke data
Proceedings of the International Symposium 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
SOUSA: sketch-based online user study applet
SBM'08 Proceedings of the Fifth Eurographics conference on Sketch-Based Interfaces and Modeling
Smart Scribbles for Sketch Segmentation
Computer Graphics Forum
Technical Section: A machine learning approach to automatic stroke segmentation
Computers and Graphics
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High quality labeled data is essential for developing and evaluating sketch recognition algorithms. Unfortunately, labeling freely-drawn sketches is time-consuming and difficult, if not impossible, using current technologies. These difficulties and the resulting lack of labeled data fundamentally limit the development of recognition algorithms. We present an intuitive, direct manipulation pen-based application for labeling sketch data in any two-dimensional domain. Our labeling tool supports the three essential sketch recognition labeling tasks: stroke fragmentation, stroke grouping and label application. Our interface integrates standard and novel interaction techniques to make each task efficient and natural. In a user study, all users felt that labeling data with our tool was quick and efficient.