A visual approach to sketched symbol recognition
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ouyang_ijcai09.pdf
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Author(s)
Davis, Randall
Ouyang, Tom Yu
Date Issued
July 2009
Journal
Proceedings of the 21st International Joint Conference on Artifical Intelligence, IJCAI '09
Publisher
Morgan Kaufmann Publishers Inc.
Citation
Tom Y. Ouyang and Randall Davis. 2009. A visual approach to sketched symbol recognition. In Proceedings of the 21st international jont conference on Artifical intelligence (IJCAI'09), Hiroaki Kitano (Ed.). Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 1463-1468.
Version
Author's final manuscript
Abstract
There is increasing interest in building systems that can automatically interpret hand-drawn sketches. However, many challenges remain in terms of recognition accuracy, robustness to different drawing styles, and ability to generalize across multiple domains. To address these challenges, we propose a new approach to sketched symbol recognition that focuses on the visual appearance of the symbols. This allows us to better handle the range of visual and stroke-level variations found in freehand drawings. We also present a new symbol classifier that is computationally efficient and invariant to rotation and local deformations. We show that our method exceeds state-of-the-art performance on all three domains we evaluated, including handwritten digits, PowerPoint shapes, and electrical circuit symbols.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
http://dl.acm.org/citation.cfm?id=1661680
