Natural error correction techniques for sketch recognition

• Main Author: Chang, Danica H. (Danica Hill)
• Other Authors: Randall Davis.
• Format: Others
• Language: English
• Published: Massachusetts Institute of Technology 2013
• Subjects: Electrical Engineering and Computer Science.
• Online Access: http://hdl.handle.net/1721.1/82371

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.