Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Traffic Sign Recognition, and Tracking Using RANSAC-Based Motion Estimation for Autonomous Vehicles

자율주행 차량을 위한 교통표지판 인식 및 RANSAC 기반의 모션예측을 통한 추적

  • Kim, Seong-Uk (Department of Industrial Engineering, Chonnam National University) ;
  • Lee, Joon-Woong (Department of Industrial Engineering, Chonnam National University)
  • 김성욱 (전남대학교 산업공학과) ;
  • 이준웅 (전남대학교 산업공학과)
  • Received : 2015.11.20
  • Accepted : 2016.01.08
  • Published : 2016.02.01
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Abstract

Autonomous vehicles must obey the traffic laws in order to drive actual roads. Traffic signs erected at the side of roads explain the road traffic information or regulations. Therefore, traffic sign recognition is necessary for the autonomous vehicles. In this paper, color characteristics are first considered to detect traffic sign candidates. Subsequently, we establish HOG (Histogram of Oriented Gradients) features from the detected candidate and recognize the traffic sign through a SVM (Support Vector Machine). However, owing to various circumstances, such as changes in weather and lighting, it is difficult to recognize the traffic signs robustly using only SVM. In order to solve this problem, we propose a tracking algorithm with RANSAC-based motion estimation. Using two-point motion estimation, inlier feature points within the traffic sign are selected and then the optimal motion is calculated with the inliers through a bundle adjustment. This approach greatly enhances the traffic sign recognition performance.

Keywords

References

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