Sunday, December 12, 2010

Reading #30: Tahuti

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  • Hammond and Davis introduce Tahuti, a geometric recognition system for UML diagrams. Among other things, Tahuti can recognize a number of different arrows and arrowheads that are part of the UML domain.

    Since I find UML to be an unnecessarily complicated and unnatural representation of a software system, I don't really care for Tahuti either.

    Reading #29: Scratch Input

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  • Scratch input is a system that does simple gesture recognition using sound data. The authors use a sensor made out of a modified stethoscope to turn any surface into a gesture input area. Users can scratch the surface with a fingernail or some other type of stylus. Only a couple gestures are supported currently.

    Using only one sensor, Scratch input is very limited in its ability to distinguish between gestures. With two or three sensors, the authors should be able to turn the sound data into a real sketch.

    Reading #28: iCanDraw?

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  • Paulson et al. introduce iCanDraw?, a system for teaching users to draw a realistic human face. The system uses computer vision techniques to automatically create a template from any image of a person's face.

    This paper does a good job of presenting "errors" to the user, and teaching the user how to correct them.

    Reading #27: KSketch

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  • Davis et al. present a sketch-based system for creating Powerpoint-like animations. Users sketch objects and then create animations for those objects, such as translation, scaling, rotation, etc.

    Since KSketch is implemented in C#, it would be cool to see it integrated into Powerpoint, as an alternative, since the authors show that it is preferred to the methods provided by Powerpoint.

    Reading #26: Picturephone

    This reading has been marked as a duplicate of reading #24.

    Reading #25: Descriptor for Image Retrieval

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  • Eitz et al. present an image descriptor that works both on a sketch (line drawing) and a processed image where the edges have been enhanced and isolated. The descriptor can be used to do sketch-based search over a large database of images.

    Merging the sketch and image worlds is a pretty cool idea. If I know vaguely what an image looks like (or what I want an image of), then I should be able to draw a quick sketch of that image and get a real image as the result.

    Reading #24: Games for Sketch Data Collection

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  • Johnson and Plimmer present several games that can be used to collect sketch data from users. In most games, sketches are created based on a textual description; participants are encouraged to make good sketches because that's how they will win the games.

    I wish SOUSA was this fun.

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