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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Wang, J., Hu, Z., Lu, H., Uchimura, K. (2006). Motion Detection in Driving Environment Using U-V-Disparity. In: Narayanan, P.J., Nayar, S.K., Shum, HY. (eds) Computer Vision – ACCV 2006. ACCV 2006. Lecture Notes in Computer Science, vol 3851. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11612032_32
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DOI: https://doi.org/10.1007/11612032_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31219-2
Online ISBN: 978-3-540-32433-1
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