Abstract
This paper deals with plane detection from a monocular image sequence without camera calibration or a priori knowledge about the egomotion. Within a framework of driver assistance applications, it is assumed that the 3D scene is a set of 3D planes. In this paper, the vision process considers obstacles, roads and buildings as planar structures. These planes are detected by exploiting iso-velocity curves after optical flow estimation. A Hough Transform-like frame called c-velocity was designed. This paper explains how this c-velocity, defined by analogy to the v-disparity in stereovision, can represent planes, regardless of their orientation and how this representation facilitates plane extraction. Under a translational camera motion, planar surfaces are transformed into specific parabolas of the c-velocity space. The error and robustness analysis of the proposed technique confirms that this cumulative approach is very efficient for making the detection more robust and coping with optical flow imprecision. Moreover, the results suggest that the concept could be generalized to the detection of other parameterized surfaces than planes.
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Bouchafa, S., Zavidovique, B. c-Velocity: A Flow-Cumulating Uncalibrated Approach for 3D Plane Detection. Int J Comput Vis 97, 148–166 (2012). https://doi.org/10.1007/s11263-011-0475-6
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DOI: https://doi.org/10.1007/s11263-011-0475-6