A note on binary template matching
Pattern Recognition
The Combinatorics of Heuristic Search Termination for Object Recognition in Cluttered Environments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Specifying gestures by example
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Recognizing multistroke geometric shapes: an experimental evaluation
UIST '93 Proceedings of the 6th annual ACM symposium on User interface software and technology
DENIM: finding a tighter fit between tools and practice for Web site design
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
SATIN: a toolkit for informal ink-based applications
UIST '00 Proceedings of the 13th annual ACM symposium on User interface software and technology
The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty
ACM Computing Surveys (CSUR)
Efficient Visual Recognition Using the Hausdorff Distance
Efficient Visual Recognition Using the Hausdorff Distance
Vision-Based Single-Stroke Character Recognition for Wearable Computing
IEEE Intelligent Systems
The Use of Grouping in Visual Object Recognition
The Use of Grouping in Visual Object Recognition
Pen and speech recognition in the user interface for mobile multimedia terminals
Pen and speech recognition in the user interface for mobile multimedia terminals
Resolving ambiguities to create a natural computer-based sketching environment
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
VizDraw: A Platform to Convert Online Hand-Drawn Graphics into Computer Graphics
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
VisionSynaptics: a system convert hand-writing and image symbol into computer symbol
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
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A long standing challenge in pen-based computer interaction is the ability to make sense of informal sketches. A main difficulty lies in reliably extracting and recognizing the intended set of visual objects from a continuous stream of pen strokes. Existing pen-based systems either avoid these issues altogether, thus resulting in the equivalent of a drawing program, or rely on algorithms that place unnatural constraints on the way the user draws. As one step toward alleviating these difficulties, we present an integrated sketch parsing and recognition approach designed to enable natural, fluid, sketch-based computer interaction. The techniques presented in this paper are oriented toward the domain of network diagrams. In the first step of our approach, the stream of pen strokes is examined to identify the arrows in the sketch. The identified arrows then anchor a spatial analysis which groups the uninterpreted strokes into distinct clusters, each representing a single object. Finally, a trainable shape recognizer, which is informed by the spatial analysis, is used to find the best interpretations of the clusters. Based on these concepts, we have built SimuSketch, a sketch-based interface for Matlab's Simulink software package. An evaluation of SimuSketch has indicated that even novice users can effectively utilize our system to solve real engineering problems without having to know much about the underlying recognition techniques.