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Sensor Fusion Based Obstacle Detection/Classification for Active Pedestrian Protection System

  • Ho Gi Jung
  • Yun Hee Lee
  • Pal Joo Yoon
  • In Yong Hwang
  • Jaihie Kim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4292)

Abstract

This paper proposes a sensor fusion based obstacle detection/classification system for active pedestrian protection system. At the front-end of vehicle, one laser scanner and one camera is installed. Clustering and tracking of range data from laser scanner generate obstacle candidates. Vision system classifies the candidates into three categories: pedestrian, vehicle, and other. Gabor filter bank extracts the feature vector of candidate image. The obstacle classification is implemented by combining two classifiers with the same architecture: support vector machine for pedestrian and vehicle. Obstacle detection system recognizing the class can actively protect pedestrian while reducing false positive rate.

Keywords

Support Vector Machine Gabor Filter Intelligent Transportation System Correct Classification Rate Vehicle Detection 
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 2006

Authors and Affiliations

  • Ho Gi Jung
    • 1
    • 2
  • Yun Hee Lee
    • 1
  • Pal Joo Yoon
    • 1
  • In Yong Hwang
    • 1
  • Jaihie Kim
    • 2
  1. 1.MANDO Corporation Central R&D CenterYongin-Si, Kyonggi-DoRepublic of Korea
  2. 2.School of Electrical and Electronic EngineeringYonsei UniversitySeoulRepublic of Korea

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