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This work presents a full generic approach to the detection and recognition of traffic signs. The approach is based on the latest computer vision methods for object detection, and on powerful methods for multiclass classification. The challenge was to robustly detect a set of different sign classes in real time, and to classify each detected sign into a large, extensible set of classes. To address this challenge, several state-of-the-art methods were developed that can be used for different recognition problems. Following an introduction to the problems of traffic sign detection and categorization, the text focuses on the problem of detection, and presents recent developments in this field. The text then surveys a specific methodology for the problem of traffic sign categorization - Error-Correcting Output Codes - and presents several algorithms, performing experimental validation on a mobile mapping application. The work ends with a discussion on future research and continuing challenges.
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This work presents a full generic approach to the detection and recognition of traffic signs. The approach, originally developed for a mobile mapping application, is based on the latest computer vision methods for object detection, and on powerful methods for multiclass classification. The challenge was to robustly detect a set of different sign classes in real time, and to classify each detected sign into a large, extensible set of classes. To address this challenge, several state-of-the-art methods were developed that can be used for different recognition problems. Following an introduction to the problems of traffic sign detection and categorization, the text focuses on the problem of detection, and presents recent developments in this field. The text then surveys a specific methodology for the problem of traffic sign categorization – Error-Correcting Output Codes – and presents several algorithms, performing experimental validation on a mobile mapping application. The work ends with a discussion on future lines of research, and continuing challenges for traffic sign recognition.
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- EditorialSpringer
- Año de publicación2011
- ISBN 10 1447122445
- ISBN 13 9781447122449
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de páginas104
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Traffic-Sign Recognition Systems
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Traffic-Sign Recognition Systems
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Traffic-Sign Recognition Systems
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Springer London, 2011
ISBN 10: 1447122445
ISBN 13: 9781447122449
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Traffic-Sign Recognition Systems
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Traffic-Sign Recognition Systems
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Traffic-Sign Recognition Systems
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Springer London Sep 2011, 2011
ISBN 10: 1447122445
ISBN 13: 9781447122449
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Traffic-Sign Recognition Systems
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Springer London, 2011
ISBN 10: 1447122445
ISBN 13: 9781447122449
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Traffic-Sign Recognition Systems
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Springer London, Springer London, 2011
ISBN 10: 1447122445
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This work presents a full generic approach to the detection and recognition of traffic signs. The approach is based on the latest computer vision methods for object detection, and on powerful methods for multiclass classification. The challenge was to robustly detect a set of different sign classes in real time, and to classify each detected sign into a large, extensible set of classes. To address this challenge, several state-of-the-art methods were developed that can be used for different recognition problems. Following an introduction to the problems of traffic sign detection and categorization, the text focuses on the problem of detection, and presents recent developments in this field. The text then surveys a specific methodology for the problem of traffic sign categorization - Error-Correcting Output Codes - and presents several algorithms, performing experimental validation on a mobile mapping application. The work ends with a discussion on future research and continuing challenges. Nº de ref. del artículo: 9781447122449
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