Journal of the Institute of Electronics and Information Engineers (전자공학회논문지)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Vehicle Recognition using Non-negative Tensor Factorization

비음수 텐서 분해를 이용한 차량 인식

  • Ban, Jae Min (Dept. of Information and Telecommunication Eng., Incheon National University) ;
  • Kang, Hyunchul (Dept. of Information and Telecommunication Eng., Incheon National University)
  • 반재민 (인천대학교 정보통신공학과) ;
  • 강현철 (인천대학교 정보통신공학과)
  • Received : 2015.03.16
  • Accepted : 2015.04.24
  • Published : 2015.05.25
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Abstract

The active control of a vehicle based on vehicle recognition is one of key technologies for the intelligent vehicle, and the part-based image representation is necessary to recognize vehicles with only partial shapes of vehicles especially in urban scene where occlusions frequently occur. In this paper, we implemented a part-based image representation scheme using non-negative tensor factorization(NTF) and realized a robust vehicle recognition system using the NTF feature. The result shows that the proposed method gives more intuitive part-based representation and more robust recognition in urban scene.

차량 인식을 기반으로 하는 능동 제어는 지능형 자동차의 구현에 필요한 핵심 기술이며. 차폐 영역(occlusion)이 빈번하게 발생하는 도심에서 차량을 인식하기 위하여 차량의 부분적인 모습만으로도 차량을 인식할 수 있는 부분 기반 차량 표현이 필요하다. 본 논문에서는 지역적인 특징을 기저벡터로 사용하는 비음수 텐서 분해(non-negative tensor factorization, NTF)를 이용하여 차량을 표현하고, NTF 분해 계수를 특징으로 차량 인식률을 검증하였다. 실험 결과, 제안하는 방법이 기존의 비음수 행렬 분해를 사용한 경우에 비하여 보다 직관적인 부분 표현이 가능하며, 도심 영상에서도 보다 강건하게 차량을 인식함을 보여주었다.

Keywords

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