Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/45493
Title: A survey on traffic light detection
Authors: Diaz, Moises 
Cerri, Pietro
Pirlo, Giuseppe
Ferrer, Miguel A. 
Impedovo, Donato
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Traffic light detection survey
Pattern Recognition
Image Processing and Computer Vision
Issue Date: 2015
Journal: Lecture Notes in Computer Science 
Conference: 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 
Abstract: 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: 9783319232218
ISSN: 0302-9743
DOI: 10.1007/978-3-319-23222-5_25
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 9281, p. 201-208
Appears in Collections:Actas de congresos
Show full item record

SCOPUSTM   
Citations

16
checked on May 9, 2021

WEB OF SCIENCETM
Citations

12
checked on May 9, 2021

Page view(s)

23
checked on May 9, 2021

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.