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Natural error correction techniques for sketch recognition

Author(s)
Chang, Danica H. (Danica Hill)
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Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Randall Davis.
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M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
Over the past few years, a plethora of tablet devices has made it very easy for users to input information by sketching as if on paper. In addition, sketch recognition systems help users convert these sketches into information that the computer understands. While lots of work has been done in developing better sketch recognizers, very little work has previously been done on how to edit the sketch once it's been drawn, whether the error is the user's or the sketch recognizer's. In response, we developed and studied intuitive methods of interacting with a sketch recognition system to correct errors made by both the recognizer and the user. The editor allows users to click and lasso to select parts of the sketch, label the selected strokes, erase by scribbling over strokes, and even overwrite errors. Letting users provide feedback to the sketch recognizer helps improve the accuracy of the sketch as well as allows the sketch recognizer's performance to improve over time.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.
 
Cataloged from PDF version of thesis.
 
Includes bibliographical references (p. 55-56).
 
Date issued
2013
URI
http://hdl.handle.net/1721.1/82371
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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