Detail publikace

Continuous Plane Detection in Point-cloud Data Based on 3D Hough Transform

Originální název

Continuous Plane Detection in Point-cloud Data Based on 3D Hough Transform

Anglický název

Continuous Plane Detection in Point-cloud Data Based on 3D Hough Transform

Jazyk

en

Originální abstrakt

In modern robotics vision systems, a shape extraction from point clouds (or depth images) is an important and still discussed  topic. We present significant optimizations of 3D Hough Transform for a plane extraction from point cloud data. The method aims to overcome noise present in these point clouds, high memory requirements for the parameter space and computational complexity of point accumulations. All these problems are further discussed and solutions are proposed to design a robust plane detector. The detector benefits from the key principle of the Hough transform, the accumulation of values in the parameter space, and processes continuous point cloud stream from the depth sensor for iterative refining of results. The proposed technique is compared against the optimized implementation of RANSAC-based plane detector in the well-known PCL library.

Anglický abstrakt

In modern robotics vision systems, a shape extraction from point clouds (or depth images) is an important and still discussed  topic. We present significant optimizations of 3D Hough Transform for a plane extraction from point cloud data. The method aims to overcome noise present in these point clouds, high memory requirements for the parameter space and computational complexity of point accumulations. All these problems are further discussed and solutions are proposed to design a robust plane detector. The detector benefits from the key principle of the Hough transform, the accumulation of values in the parameter space, and processes continuous point cloud stream from the depth sensor for iterative refining of results. The proposed technique is compared against the optimized implementation of RANSAC-based plane detector in the well-known PCL library.

BibTex


@article{BUT103422,
  author="Rostislav {Hulík} and Michal {Španěl} and Zdeněk {Materna} and Pavel {Smrž}",
  title="Continuous Plane Detection in Point-cloud Data Based on 3D Hough Transform",
  annote="In modern robotics vision systems, a shape extraction from point clouds (or depth
images) is an important and still discussed  topic. We present significant
optimizations of 3D Hough Transform for a plane extraction from point cloud data.
The method aims to overcome noise present in these point clouds, high memory
requirements for the parameter space and computational complexity of point
accumulations. All these problems are further discussed and solutions are
proposed to design a robust plane detector. The detector benefits from the key
principle of the Hough transform, the accumulation of values in the parameter
space, and processes continuous point cloud stream from the depth sensor for
iterative refining of results. The proposed technique is compared against the
optimized implementation of RANSAC-based plane detector in the well-known PCL
library.",
  address="NEUVEDEN",
  booktitle="Visual Understanding and Applications with RGB-D Cameras",
  chapter="103422",
  doi="10.1016/j.jvcir.2013.04.001",
  edition="NEUVEDEN",
  howpublished="print",
  institution="NEUVEDEN",
  number="1",
  volume="25",
  year="2013",
  month="april",
  pages="86--97",
  publisher="NEUVEDEN",
  type="journal article - other"
}