Authors:
- Presents a full generic approach to the detection and recognition of traffic signs, based on state-of-the-art computer vision methods for object detection, and on powerful methods for multiclass classification
- Surveys a specific methodology for the problem of traffic sign categorization: Error-Correcting Output Codes
- Includes experimental validation results performed on a mobile mapping application
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)
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Table of contents (6 chapters)
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Front Matter
About this book
Authors and Affiliations
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Dept. of Applied Mathematics & Analysis, University of Barcelona, Barcelona, Spain
Sergio Escalera
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Universitat Oberta de Catalunya, Department of Computer Science, Rambla del Poblenou, Spain
Xavier Baró
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Dept of Applied Mathematics and Analysis, University of Barcelona, Gran Via de les Corts Catalanes, Spain
Oriol Pujol
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University of Barcelona, Dept of Applied Mathematics and Analysis, Gran Via de les Corts Catalanes, Spain
Jordi Vitrià, Petia Radeva
Bibliographic Information
Book Title: Traffic-Sign Recognition Systems
Authors: Sergio Escalera, Xavier Baró, Oriol Pujol, Jordi Vitrià, Petia Radeva
Series Title: SpringerBriefs in Computer Science
DOI: https://doi.org/10.1007/978-1-4471-2245-6
Publisher: Springer London
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Sergio Escalera 2011
Softcover ISBN: 978-1-4471-2244-9Published: 23 September 2011
eBook ISBN: 978-1-4471-2245-6Published: 22 September 2011
Series ISSN: 2191-5768
Series E-ISSN: 2191-5776
Edition Number: 1
Number of Pages: VI, 96
Number of Illustrations: 34 b/w illustrations
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