TR2009-027

A New Approach for In-Vehicle Camera Traffic Sign Detection and Recognition


    •  Ruta, A., Porikli, F., Li, Y., Watanabe, S., Kage, H., Sumi, K., "A New Approach for In-Vehicle Camera Traffic Sign Detection and Recognition", IAPR Conference on Machine vision Applications (MVA), May 2009.
      BibTeX TR2009-027 PDF
      • @inproceedings{Ruta2009may,
      • author = {Ruta, A. and Porikli, F. and Li, Y. and Watanabe, S. and Kage, H. and Sumi, K.},
      • title = {A New Approach for In-Vehicle Camera Traffic Sign Detection and Recognition},
      • booktitle = {IAPR Conference on Machine vision Applications (MVA)},
      • year = 2009,
      • month = may,
      • url = {https://www.merl.com/publications/TR2009-027}
      • }
  • Research Areas:

    Artificial Intelligence, Computer Vision, Machine Learning

Abstract:

In this paper we discuss theoretical foundations and a practical realization of a circular traffic sign detection and recognition system operating on board of a vehicle. To initially detect sign candidates in the scene, we utilize the circular Hough transform with an appropriate post-processing in the vote space. Track of an already established candidate is maintained using a function that encodes the relationship between a unique feature representation of the target object and the affine transinformation it is subject to. This function is learned on-the-fly via regression from random distortions applied to the last stable image of the sign. Finally, we adopt a novel AdaBoost algorithm to learn a sign similarity measure from example image pairs labeled either \"same\" or \"different\". This enables construction of an efficient multi-class classifier. Prototype implementation has been evaluated on a video captured in crowded street scenes. Good detection and recognition performance was achieved for a 14 class problem which reveals a high potential of our approach.

 

  • Related News & Events

    •  NEWS    MVA 2009: publication by MERL researchers and others
      Date: May 20, 2009
      Where: IAPR Conference on Machine vision Applications (MVA)
      Research Area: Machine Learning
      Brief
      • The paper "A New Approach for In-Vehicle Camera Traffic Sign Detection and Recognition" by Ruta, A., Porikli, F., Li, Y., Watanabe, S., Kage, H. and Sumi, K. was presented at the IAPR Conference on Machine vision Applications (MVA).
    •