Real Time Visual Traffic Lights Recognition Based on Spot Light Detection and Adaptive Traffic Lights Templates

机译：基于聚光灯检测和自适应交通信号灯模板的实时视觉交通信号灯识别

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This paper introduces a new real-time traffic light recognition system for on-vehicle camera applications. This approach has been tested with good results in urban scenes. Thanks to the use of our generic “Adaptive Templates” it would be possible to recognize different kinds of traffic lights from various countries. Our approach is mainly based on a spot detection algorithm therefore able to detect lights from a high distance with the main advantage of being not so sensitive to motion blur and illumination variations. The detected spots together with other shape analysis form strong hypothesis we feed our Adaptive Templates Matcher with. Even though it is still in progress, our system was validated in real conditions in our prototype vehicle and also using registered video sequences. We noticed a high rate of correctly recognized traffic lights and very few false alarms. Processing is performed in real-time on 640x480 images using a 2.9GHz single core desktop computer.

机译：本文介绍了一种用于车载摄像头应用的新型实时交通信号灯识别系统。该方法已在城市场景中进行了测试，效果良好。由于使用了通用的“自适应模板”，因此可以识别来自不同国家的不同类型的交通信号灯。我们的方法主要基于点检测算法，因此能够从远距离检测光，其主要优点是对运动模糊和照明变化不太敏感。所检测到的斑点与其他形状分析一起构成了强有力的假设，我们将其提供给自适应模板匹配器。即使仍在进行中，我们的系统也已在原型车的真实条件下进行了验证，并使用了已注册的视频序列。我们注意到正确识别交通信号灯的比率很高，很少出现错误警报。使用2.9GHz单核台式计算机对640x480图像进行实时处理。

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《World congress and exhibition on intelligent transport systems and services;ITS world congress》|2009年|p.1-12|共12页
会议地点 Stockholm(SE);Stockholm(SE)
作者
Raoul de Charette; Fawzi Nashashibi;
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作者单位

Robotics Center (CAOR) Ecole des mines de Paris (ParisTech) 60bd Saint Michel F-75272 Paris cedex06 France. Phone : (33)1-40.51.94.54 (e-mail : raoul.de_charette@ensmp.fr);

INRIA Imara Team BP 105 78153 Le Chesnay Cedex France. Phone : (33)1-39-63-52-56 (e-mail : fawzi.nashashibi@ensmp.fr);

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关键词
Intelligent vehicles; ADAS; traffic lights; traffic signs; light detection; template; template matching; adaptive template;

机译：智能汽车； ADAS；红绿灯;交通标识;光检测；模板;模板匹配；自适应模板;

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专利

1. Saliency Map Generation by the Convolutional Neural Network for Real-Time Traffic Light Detection Using Template Matching [J] . John Vijay, Yoneda Keisuke, Liu Zheng, Computational Imaging, IEEE Transactions on . 2015,第3期

机译：通过卷积神经网络生成显着图，用于使用模板匹配的实时交通信号灯检测
2. Research and Practice of Traffic Lights and Traffic Signs Recognition System Based on Multicore of FPGA [J] . Shuhe Wang, Pan Zhang, Zhitao Dai, Communications and Network . 2013,第1期

机译：基于FPGA多核的交通信号灯与交通标志识别系统的研究与实践
3. Real-Time Traffic Light Detection With Adaptive Background Suppression Filter [J] . Zhenwei Shi, Zhengxia Zou, Changshui Zhang IEEE Transactions on Intelligent Transportation Systems . 2016,第3期

机译：自适应背景抑制滤波器的实时交通信号灯检测
4. Real time visual traffic lights recognition based on Spot Light Detection and adaptive traffic lights templates [C] . de Charette R., Nashashibi F. IEEE Intelligent Vehicles Symposium . 2009

机译：基于聚光灯检测和自适应交通信号灯模板的实时视觉交通信号灯识别
5. Daytime running lights: An evaluation of the impact on traffic safety. [D] . Tofflemire, Troy Craig. 1995

机译：日间行车灯：对交通安全影响的评估。
6. Lightweight PVIDNet: A Priority Vehicles Detection Network Model Based on Deep Learning for Intelligent Traffic Lights [O] . Rodrigo Carvalho Barbosa, Muhammad Shoaib Ayub, Renata Lopes Rosa, 2020

机译：轻量级PVIDNet：优先车辆检测网络模型基于深度学习智能红绿灯
7. Traffic flow on realistic road networks with adaptive traffic lights [O] . de Gier, Jan, Garoni, Timothy M, Rojas, Omar 2011

机译：在现实路网的交通流量与自适应红绿灯

Real Time Visual Traffic Lights Recognition Based on Spot Light Detection and Adaptive Traffic Lights Templates

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