A hybrid approach of candidate region extraction for robust traffic light recognition

In this paper, we consider the problem of recognizing circular traffic lights from an image. The traffic light recognition is divided into two stages: candidate region extraction and traffic light recognition. For extracting candidates, we propose a hybrid method, which combines the results of spotlight detection and color-shape model-based method. Instead of handcrafting a set of features for classification, we scale each candidate as a 10-by-10 image patch and use its raw RGB pixel values as the input of a Support Vector Machine (SVM) classifier. The classifiers are trained only using a Singapore dataset, and are tested on the US LISA dataset. The cross validation justifies the generalizability of our classifiers. The evaluation results show that our hybrid candidate extraction method lowers the chance of miss-detection and the proposed featureless classification approach has a high recognition precision. Our algorithm is robust and efficient, which can run at 30 fps for images with a resolution of 640∗480.

[1]  Zheng Liu,et al.  Traffic light recognition in varying illumination using deep learning and saliency map , 2014, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[2]  Mohan M. Trivedi,et al.  Traffic Light Detection: A Learning Algorithm and Evaluations on Challenging Dataset , 2015, 2015 IEEE 18th International Conference on Intelligent Transportation Systems.

[3]  Toshiaki Kondo,et al.  Red traffic light detection using fast radial symmetry transform , 2014, 2014 11th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON).

[4]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[5]  Gang Tao,et al.  The recognition and tracking of traffic lights based on color segmentation and CAMSHIFT for intelligent vehicles , 2010, 2010 IEEE Intelligent Vehicles Symposium.

[6]  Ho Gi Jung,et al.  Enhancing Light Blob Detection for Intelligent Headlight Control Using Lane Detection , 2013, IEEE Transactions on Intelligent Transportation Systems.

[7]  Pietro Cerri,et al.  Traffic Light Recognition During the Night Based on Fuzzy Logic Clustering , 2013, EUROCAST.

[8]  Umit Ozguner,et al.  A robust video based traffic light detection algorithm for intelligent vehicles , 2009, 2009 IEEE Intelligent Vehicles Symposium.

[9]  Fawzi Nashashibi,et al.  Traffic light recognition using image processing compared to learning processes , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  Qijun Chen,et al.  Traffic Light Detection Based on Multi-feature Segmentation and Online Selecting Scheme , 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[11]  Jin-Hyung Park,et al.  Real-Time Signal Light Detection , 2008, 2008 Second International Conference on Future Generation Communication and Networking Symposia.

[12]  Ralf G. Herrtwich,et al.  Making Bertha See , 2013, 2013 IEEE International Conference on Computer Vision Workshops.

[13]  Yang Yi,et al.  A framework of traffic lights detection, tracking and recognition based on motion models , 2014, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[14]  Ju H. Park,et al.  Night-Time Traffic Light Detection Based On SVM with Geometric Moment Features , 2013 .

[15]  Edward Jones,et al.  Rear-Lamp Vehicle Detection and Tracking in Low-Exposure Color Video for Night Conditions , 2010, IEEE Transactions on Intelligent Transportation Systems.

[16]  Chris Urmson,et al.  Traffic light mapping and detection , 2011, 2011 IEEE International Conference on Robotics and Automation.

[17]  Shinichiro Omachi,et al.  Detection of traffic light using structural information , 2010, IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS.

[18]  Evangeline Pollard,et al.  Tracking both pose and status of a traffic light via an Interacting Multiple Model filter , 2014, 17th International Conference on Information Fusion (FUSION).

[19]  Sebastian Thrun,et al.  Traffic light mapping, localization, and state detection for autonomous vehicles , 2011, 2011 IEEE International Conference on Robotics and Automation.

[20]  大町 真一郎,et al.  Traffic Light Detection with Color and Edge Information , 2009 .

[21]  Dwi H. Widyantoro,et al.  Traffic lights detection and recognition based on color segmentation and circle hough transform , 2015, 2015 International Conference on Data and Software Engineering (ICoDSE).

[22]  Marc Schlipsing,et al.  Extending traffic light recognition: Efficient classification of phase and pictogram , 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

[23]  Myoungho Sunwoo,et al.  Multiple exposure images based traffic light recognition , 2014, 2014 IEEE Intelligent Vehicles Symposium Proceedings.

[24]  Javier J. Sánchez Medina,et al.  Suspended traffic lights detection and distance estimation using color features , 2012, 2012 15th International IEEE Conference on Intelligent Transportation Systems.

[25]  Mohan M. Trivedi,et al.  Vision for Looking at Traffic Lights: Issues, Survey, and Perspectives , 2016, IEEE Transactions on Intelligent Transportation Systems.

[26]  Jae Wook Jeon,et al.  Real-time traffic light detection using color density , 2016, 2016 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia).

[27]  Changshui Zhang,et al.  Real-Time Traffic Light Detection With Adaptive Background Suppression Filter , 2016, IEEE Transactions on Intelligent Transportation Systems.

[28]  Fawzi Nashashibi,et al.  Real time visual traffic lights recognition based on Spot Light Detection and adaptive traffic lights templates , 2009, 2009 IEEE Intelligent Vehicles Symposium.

[29]  Klaus C. J. Dietmayer,et al.  A closer look on traffic light detection evaluation metrics , 2016, 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC).

[30]  Johann Marius Zöllner,et al.  Visual state estimation of traffic lights using hidden Markov models , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[31]  Adrian Kaehler,et al.  Learning OpenCV, 2nd Edition , 2014 .

[32]  Xinming Huang,et al.  Automatic detection of traffic lights using support vector machine , 2015, 2015 IEEE Intelligent Vehicles Symposium (IV).