Journal of Platform Technology

  • 제6권4호
  • /
  • Pages.18-25
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  • 2018
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  • 2289-0181(pISSN)
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  • 2289-019X(eISSN)
ICT플랫폼학회 (ICT Platform Society)
권호 표지

Human and Robot Tracking Using Histogram of Oriented Gradient Feature

  • 투고 : 2018.11.26
  • 심사 : 2018.12.26
  • 발행 : 2018.12.31

⟨ 이전 논문 다음 논문 ⟩

초록

This paper describes a real-time human and robot tracking method in Intelligent Space with multi-camera networks. The proposed method detects candidates for humans and robots by using the histogram of oriented gradients (HOG) feature in an image. To classify humans and robots from the candidates in real time, we apply cascaded structure to constructing a strong classifier which consists of many weak classifiers as follows: a linear support vector machine (SVM) and a radial-basis function (RBF) SVM. By using the multiple view geometry, the method estimates the 3D position of humans and robots from their 2D coordinates on image coordinate system, and tracks their positions by using stochastic approach. To test the performance of the method, humans and robots are asked to move according to given rectangular and circular paths. Experimental results show that the proposed method is able to reduce the localization error and be good for a practical application of human-centered services in the Intelligent Space.

키워드

과제정보

연구 과제 주관 기관 : National Research Foundation of Korea(NRF)

참고문헌

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