Munich, Mario E. and Perona, Pietro (1996) Visual input for pen-based computers. In: Proceedings of the 13th International Conference on Pattern Recognition, 1996. Vol.3. IEEE , Piscataway, NJ, pp. 33-37. ISBN 0-8186-7282-X. https://resolver.caltech.edu/CaltechAUTHORS:20140730-101723057
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Abstract
Handwriting may be captured using a video camera, rather than the customary pressure-sensitive tablet. This paper presents a simple system based on correlation and recursive prediction methods that can track the tip of the pen in real time with sufficient spatio-temporal resolution and accuracy to enable handwritten character recognition. The system is tested on a large and heterogeneous set of examples and its performance is compared to that of three human operators and a commercial high-resolution pressure-sensitive tablet.
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| Additional Information: | © 1996 IEEE. This work is supported in part by the Center for Neuromorphic Systems Engineering as a part of the National Science Foundation Engineering Research Center Program; and by the California Trade and Commerce Agency, Office of Strategic Technology. We wish to thank all the persons that helped us throughout this work, in especially Jean-Yves Bouguet (who wrote many words for us), Stefano Soatto, and Luis Goncalves for the very useful discussions. | |||||||||
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| Subject Keywords: | active vision, computer vision, handwriting recognition, optical character recognition, Systems and applications, Active and real-time vision, Handwriting acquisition | |||||||||
| DOI: | 10.1109/ICPR.1996.546790 | |||||||||
| Record Number: | CaltechAUTHORS:20140730-101723057 | |||||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20140730-101723057 | |||||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | |||||||||
| ID Code: | 47644 | |||||||||
| Collection: | CaltechAUTHORS | |||||||||
| Deposited By: | Caroline Murphy | |||||||||
| Deposited On: | 04 Aug 2014 21:35 | |||||||||
| Last Modified: | 10 Nov 2021 17:48 |
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