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单视未标定图像的正交灭点检测算法

  

  1. 南昌航空大学软件学院
  • 出版日期:2016-12-31 发布日期:2017-01-05
  • 基金资助:
    国家自然科学基金项目(61263046)

Un-Calibrated Single Visual Image of Orthogonal Vanishing Point Detection Algorithm

  1. School of Software, Nanchang Hangkong University
  • Online:2016-12-31 Published:2017-01-05

摘要: 传统方法只能计算标定图像的正交灭点,同时没有考虑图像直线检测结果的误差、
直线的长度以及候选灭点与约束直线之间的位置关系对灭点检测精度的影响。针对此类问题,
提出了一种针对单视未标定图像的正交灭点检测方法。首先利用J-Linkage 完成灭点的初始化估
计,得到假设灭点集合;然后根据假设灭点与图像直线之间的一致性约束、图像直线的长度,
基于投票机制先得到精确的垂直方向灭点;后利用灭点、灭线的定义和性质,计算得到图像相
机参数;根据正交灭点的特性,得到准确的水平方向和纵深方向的灭点。因引入了一种新的假
设灭点和图像直线之间的一致性度量方法,正交灭点检测精度不受直线检测结果的误差、直线
的长度以及候选灭点与约束直线之间的位置关系的影响,在未知图像相机参数的情况下能精准
的得到三个正交灭点信息。正交灭点检测方法在室内场景下可以得到更加精确的检测结果。

关键词: 单视图像, 未标定, 投票, 正交灭点, N 矢量

Abstract: The traditional method can only calculate the orthogonal vanishing point of the calibration
image, dose not take into account the error of straight line detection, the length of the straight line and
the location relationship between the candidate vanishing point and the constrained line has the
impact on the accuracy of the vanishing point detection. For such problems, this paper proposes an
un-calibrated single visual image of orthogonal vanishing point detection algorithm. First, use
J-Linkage algorithm to complete the initialization of the vanishing point estimates, and get the set of
assumed vanishing points. Second, according to the consistency between the assumed vanishing
points and lines, length of line segment to get the exact vertical vanishing point based on a voting
mechanism. Third, calculate the parameters of the image camera by the nature and properties of the
vanishing point and vanishing line. Then based of the orthogonal characteristics of the vanishing point
to get the exact horizontal and depth direction of the vanishing point. By the introduction of a new
consistency measurement method between the assumed vanishing point and the line of image, this
method not only gets rid of the dependence on the camera parameters, but also reduces the impacts of
the impacts of errors of line segment extraction, length of line segment as well as the relative position of
vanishing point and the constrained line on the precision of vanishing points detection, in the case of unknown image camera parameters this method can get accurate information about the three orthogonal
vanishing point. This method this thesis applied can achieve better results in indoor scenes.

Key words: single visual image, un-calibrated, voting, orthogonal vanishing points, N-vectors