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Visual input for pen-based computers

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.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1109/ICPR.1996.546790DOIArticle
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=546790PublisherArticle
ORCID:
AuthorORCID
Munich, Mario E.0000-0002-6665-7473
Perona, Pietro0000-0002-7583-5809
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.
Funders:
Funding AgencyGrant Number
NSFUNSPECIFIED
California Trade and Commerce Agency, Office of Strategic TechnologyUNSPECIFIED
Center for Neuromorphic Systems Engineering, CaltechUNSPECIFIED
Subject Keywords:active vision, computer vision, handwriting recognition, optical character recognition, Systems and applications, Active and real-time vision, Handwriting acquisition
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:03 Oct 2019 06:55

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