Vision-Based Traffic Light Detection for Intelligent Vehicles

Vision-based traffic light detection has been widely studied over the past decade. However, it is still a challenging task to build a real-time and robust classifier-based detector without a high dependency on prior knowledge. In this paper, we have a deep look at the design of features and detectio...

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Bibliographic Details
Published in2017 4th International Conference on Information Science and Control Engineering (ICISCE) pp. 1323 - 1326
Main Authors Du, Xiaoping, Li, Yang, Guo, Yuang, Xiong, Hui
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2017
Subjects
aggregate channel features
Aggregates
Algorithm design and analysis
boosted trees
Detectors
Feature extraction
Histograms
Image color analysis
traffic light detection
Training
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Summary:Vision-based traffic light detection has been widely studied over the past decade. However, it is still a challenging task to build a real-time and robust classifier-based detector without a high dependency on prior knowledge. In this paper, we have a deep look at the design of features and detection mechanism in the domain of traffic light detection; propose a multi-scale and multi-phase detector based on aggregate channel features and boosted trees classifier. Evaluation is done on Daimler, LISA and LaRA datasets, which shows high average-recall and speed. Code has been made publicly available.
DOI:10.1109/ICISCE.2017.275