Obstacles Extraction Using a Moving Camera

  • Shaohua Qian
  • Joo Kooi Tan
  • Hyoungseop Kim
  • Seiji Ishikawa
  • Takashi Morie
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7729)


A method of automatic obstacles detection is proposed which employs a camera mounted on a vehicle. Although various methods of obstacles detection have already been reported, they normally detect moving objects such as pedestrians and bicycles. In this paper, a method is proposed for detecting obstacles on a road, irrespective of moving or static, by the employment of the background modeling and the road region classification. The background modeling is often used to detect moving objects when a camera is static. In this paper, we apply it to the moving camera case to get foreground images. Then we extract the road region using SVM. In this road region, we carry out region classification. Then we can delete all the things which are not obstacles in the foreground images using the result of the region classification. In the performed experiments, it is shown that the proposed method is able to extract the shapes of both static and moving obstacles in a frontal view from a car.


Support Vector Machine Gaussian Mixture Model Motion Compensation Obstacle Detection Virtual Scene 
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 2013

Authors and Affiliations

  • Shaohua Qian
    • 1
  • Joo Kooi Tan
    • 1
  • Hyoungseop Kim
    • 1
  • Seiji Ishikawa
    • 1
  • Takashi Morie
    • 2
  1. 1.Department of Mechanical & Control EngineeringKyushu Institute of TechnologyJapan
  2. 2.School of Brain Science & EngineeringKyushu Institute of TechnologyJapan

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