In this paper, we propose a method to construct an accurate traffic sign detector with a small number of manual interactions. When using a statistical learning approach, a huge number of training samples should be prepared for constructing an accurate detector. However, in a real environment, traffic signs have various appearances, and their backgrounds vary widely, too. Therefore, it is very difficult and expensive to manually collect all possible views. Co-training is one of the semi-supervised learning techniques, that can collect training samples efficiently and automatically by using multiple classifiers. In this paper, we employ this approach for improving the accuracy of a traffic sign detector with low cost. The main contributions of this paper are the extension of the co-training method by introducing a majority voting scheme, and the introduction of this framework for improving the accuracy of traffic sign detection. By using this voting type co-training, the proposed method gathers traffic sign samples automatically and accurately, and improves the performance of the traffic sign detector. Experimental results showed that the proposed method improved the accuracy of the detector with a maximum F-measure of 0.95 from 0.72.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Construction of a traffic sign detector based on voting type co-training


    Contributors:


    Publication date :

    2013-10-01


    Size :

    1970124 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    A Single Target Voting Scheme for Traffic Sign Detection

    Houben, S. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2011


    Intelligent Traffic Sign Detector: Adaptive Learning Based on Online Gathering of Training Samples

    Deguchi, D. / Shirasuna, M. / Doman, K. et al. | British Library Conference Proceedings | 2011


    LIGHT TYPE TRAFFIC SIGN MANAGEMENT SYSTEM

    CHOI GYU YEONG / LIM DONG KUN | European Patent Office | 2016

    Free access

    Construction method of slow traffic driving road sign

    WANG WEI | European Patent Office | 2022

    Free access

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

    Deguchi, D. / Doman, K. / Ide, I. et al. | British Library Conference Proceedings | 2011