2026-09-19T08:49:35Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/823712022-01-13T07:54:01Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Randall Davis.
Chang, Danica H. (Danica Hill)
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2013-11-18T19:14:55Z
2013-11-18T19:14:55Z
2013
2013
http://hdl.handle.net/1721.1/82371
862074582
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).
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.
by Danica H. Chang.
S.M.
56 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Natural error correction techniques for sketch recognition
Thesis
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Publication
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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.</Abstract>
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