Hough Parameter Space Regularisation for Line Detection in 3D

Manuel Jeltsch, Christoph Dalitz, Regina Pohle-Fröhlich
2016 Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications  
The Hough transform is a well known technique for detecting lines or other parametric shapes in point clouds. When it is used for finding lines in a 3D-space, an appropriate line representation and quantisation of the parameter space is necessary. In this paper, we address the problem that a straightforward quantisation of the optimal four-parameter representation of a line after Roberts results in an inhomogeneous tessellation of the geometric space that introduces bias with respect to certain
more » ... line orientations. We present a discretisation of the line directions via tessellation of an icosahedron that overcomes this problem whenever one parameter in the Hough space represents a direction in 3D (e.g. for lines or planes). The new method is applied to the detection of ridges and straight edges in laser scan data of buildings, where it performs better than a straightforward quantisation.
doi:10.5220/0005679003450352 dblp:conf/visapp/JeltschDP16 fatcat:xaxtxj73zng47ovciqyjmpof6q