Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/45493
| Título: | A survey on traffic light detection | Autores/as: | Diaz, Moises Cerri, Pietro Pirlo, Giuseppe Ferrer, Miguel A. Impedovo, Donato |
Clasificación UNESCO: | 3307 Tecnología electrónica | Palabras clave: | Traffic light detection survey Pattern Recognition Image Processing and Computer Vision |
Fecha de publicación: | 2015 | Editor/a: | Springer | Publicación seriada: | Lecture Notes in Computer Science | Conferencia: | 18th International Conference on Image Analysis and Processing (ICIAP) 18th International Conference on Image Analysis and Processing, ICIAP 2015 BioFor, CTMR, RHEUMA, ISCA, MADiMa, SBMI, and QoEM |
Resumen: | Traffic light detection is an important matter in urban environments during the transition to fully autonomous driving. Many literature has been generated in the recent years approaching different pattern recognition strategies. In this paper we present a survey summarizing relevant works in the field of detection of both suspended and supported traffic light. This survey organizes different methods highlighting main reasearch areas in the computer vision field. | URI: | http://hdl.handle.net/10553/45493 | ISBN: | 978-3-319-23221-8 | ISSN: | 0302-9743 | DOI: | 10.1007/978-3-319-23222-5_25 | Fuente: | New Trends in Image Analysis and Processing -- ICIAP 2015 Workshops. ICIAP 2015. Lecture Notes in Computer Science, v. 9281 LNCS, p. 201-208 |
| Colección: | Capítulo de libro |
Citas SCOPUSTM
32
actualizado el 01-dic-2024
Citas de WEB OF SCIENCETM
Citations
25
actualizado el 24-nov-2024
Visitas
80
actualizado el 12-may-2024
Google ScholarTM
Verifica
Altmetric
Comparte
Exporta metadatos
Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.