Motion detection in driving environment using u-v-disparity

  • Authors:

  • Jia Wang;Zhencheng Hu;Hanqing Lu;Keiichi Uchimura

  • Affiliations:

  • National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;Department of Computer Science, Kumamoto University, Kumamoto, Japan;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;Department of Computer Science, Kumamoto University, Kumamoto, Japan

  • Venue:
  • ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
  • Year:
  • 2006

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Abstract

Motion detection in driving environment, which aims to detect REAL moving objects from continuously changing background, is vital for Adaptive Cruise Control (ACC) applications. This paper presents an efficient solution for such problem using a stereovision based method. First, a comprehensive analysis about 3D global motion is given based on ”U-V-disparity” concept, in which a 5-parameter model is deduced to describe global motion within U-V-disparity domain and an iterative Least Square Estimation method is proposed to estimate the parameters. Then, in order to identify separate objects, geometric analysis segments the road scene into 3D object-surfaces based on U-V-disparity features of road surfaces, roadside structures and obstacles. Finally, the motions of the segmented object-surfaces are compared with the estimated global motion to find REAL moving surfaces, which correspond to the real moving objects. The proposed algorithm has been tested on real road sequences and experimental results verified its efficiency.