Journal of Multimedia Information System

Korea Multimedia Society (한국멀티미디어학회)
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Two-wheeler Detection System using Histogram of Oriented Gradients based on Local Correlation Coefficients and Curvature

  • Lee, Yeunghak (Avioics Electronic Engineering, Kyungwoon University) ;
  • Kim, Taesun (Avioics Electronic Engineering, Kyungwoon University) ;
  • Shim, Jaechang (Computer Engineering, Andong National University)
  • Received : 2016.02.03
  • Accepted : 2016.02.23
  • Published : 2015.12.31
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Abstract

Vulnerable road users such as bike, motorcycle, small automobiles, and etc. are easily attacked or threatened with bigger vehicles than them. So this paper suggests a new approach two-wheelers detection system riding on people based on modified histogram of oriented gradients (HOGs) which is weighted by curvature and local correlation coefficient. This correlation coefficient between two variables, in which one is the person riding a bike and other is its background, can represent correlation relation. First, we extract edge vectors using the curvature of Gaussian and Histogram of Oriented Gradients (HOG) which includes gradient information and differential magnitude as cell based. And then, the value, which is calculated by the correlation coefficient between the area of each cell and one of bike, can be used as the weighting factor in process for normalizing the HOG cell. This paper applied the Adaboost algorithm to make a strong classification from weak classification. The experimental results validate the effectiveness of our proposed algorithm show higher than that of the traditional method and under challenging, such as various two-wheeler postures, complex background, and even conclusion.

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References

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