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Improvement of a Traffic Sign Detector by Retrospective Gathering of Training Samples from In-Vehicle Camera Image Sequences

  • Daisuke Deguchi
  • Keisuke Doman
  • Ichiro Ide
  • Hiroshi Murase
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6469)

Abstract

This paper proposes a method for constructing an accurate traffic sign detector by retrospectively obtaining training samples from in-vehicle camera image sequences. To detect distant traffic signs from in-vehicle camera images, training samples of distant traffic signs are needed. However, since their sizes are too small, it is difficult to obtain them either automatically or manually. When driving a vehicle in a real environment, the distance between a traffic sign and the vehicle shortens gradually, and proportionally, the size of the traffic sign becomes larger. A large traffic sign is comparatively easy to detect automatically. Therefore, the proposed method automatically detects a large traffic sign, and then small traffic signs (distant traffic signs) are obtained by retrospectively tracking it back in the image sequence. By also using the retrospectively obtained traffic sign images as training samples, the proposed method constructs an accurate traffic sign detector automatically. From experiments using in-vehicle camera images, we confirmed that the proposed method could construct an accurate traffic sign detector.

Keywords

Training Sample Sign Detector Face Detection Sign Image Traffic Sign 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Daisuke Deguchi
    • 1
  • Keisuke Doman
    • 1
  • Ichiro Ide
    • 1
  • Hiroshi Murase
    • 1
  1. 1.Graduate School of Information ScienceNagoya UniversityNagoyaJapan

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