一种快速的人工场景图像消失点检测方法

A fast vanishing point detection method for artificial scene image

人工场景中包含了大量的空间平行线以及垂直边,这些空间平行线映射到图像中相交产生的交点即消失点。消失点检测对摄像机标定、三维场景重建等都有着重要的意义。传统的消失点检测算法往往基于二维霍夫参数空间,复杂度高、效率低。因此,提出一种新的方法,先检测图像中较长的边界线,并将检测到的线段进行筛选、分组;然后利用消失点与焦距之间的制约关系,确定三向消失点的位置以及焦距的大小。该方法将传统的二维霍夫参数空间转换为二级一维霍夫参数空间。实验表明,这种方法运算复杂度低、运行时间短。在室外场景图像中,鲁棒性好,且保持较高的准确率。

Artificial scenes contain many parallel lines and orthogonal edges. These parallel lines pro- jected onto lines in the image will meet in a common point. This point of intersection is the vanishing point. Vanishing point detection is of important significance for camera calibration, 3D scene reconstruc- tion and so on. Traditional vanishing point detection algorithms are always based on 2D Hough parameter space. The complexity is high and the efficiency is low. Therefore a novel method is proposed. Firstly, long straight edges are detected followed by selecting and grouping these lines. Secondly, the constraints of relationship between vanishing point and focal length are used to get specific location of the vanishing points. The method decomposes a 2D Hough parameter space into two cascaded 1D Hough pa- rameter spaces. Experiments show that this method has lower complexity and shorter running time. In outdoor artificial scene images, it performs more robust and accurate.