article

The 3D Hough Transform for plane detection in point clouds: A review and a new accumulator design

Authors:

Dorit Borrmann,

Andreas NüchterAuthors Info & Claims

3D Research, Volume 2, Issue 2

Article No.: 32, Pages 1 - 13

https://doi.org/10.1007/3DRes.02(2011)3

Published: 01 March 2011 Publication History

Abstract

The Hough Transform is a well-known method for detecting parameterized objects. It is the de facto standard for detecting lines and circles in 2-dimensional data sets. For 3D it has attained little attention so far. Even for the 2D case high computational costs have lead to the development of numerous variations for the Hough Transform. In this article we evaluate different variants of the Hough Transform with respect to their applicability to detect planes in 3D point clouds reliably. Apart from computational costs, the main problem is the representation of the accumulator. Usual implementations favor geometrical objects with certain parameters due to uneven sampling of the parameter space. We present a novel approach to design the accumulator focusing on achieving the same size for each cell and compare it to existing designs.

References

[1]

M. A. Fischler, R. C. Bolles (1981) Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography, Communications of the ACM . 24 :381-395.

Digital Library

[2]

R. Schnabel, R. Wahl, R. Klein (2007) Efficient RANSAC for Point-Cloud Shape Detection, Computer Graphics Forum .

[3]

U. Bauer, K. Polthier (2008) Detection of Planar Regions in Volume Data for Topology Optimization, Lecture Notes in Computer Science .

Digital Library

[4]

J. Poppinga, N. Vaskevicius, A. Birk, K. Pathak (2008) Fast Plane Detection and Polygonalization in noisy 3D Range Images, In IROS '08 .

[5]

R. Lakaemper, L. J. Latecki (2006) Extended EM for Planar Approximation of 3D Data, In IEEE International Conference on Robotics and Automation (ICRA '06) .

[6]

O. Wulf, K. O. Arras, H. I. Christensen, B. A. Wagner (2004) 2D Mapping of Cluttered Indoor .

[7]

G. Yu, M. Grossberg, G. Wolberg, I. Stamos (2008) Think Globally, Cluster Locally: A Unified Framework for Range Segmentation, In Proceedings of the 4th International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT '08), Atlanta, USA .

[8]

M. Attene, B. Falcidieno, M. Spagnuolo (2006) Hierarchical mesh segmentation based on fitting primitives, The Visual Computer . 22 :181-193.

Digital Library

[9]

P. V. C. Hough (1962) Method and Means for Recognizing Complex Patterns, US Patent 3069654 .

[10]

R. O. Duda, P. E. Hart (1971) Use of the Hough Transformation to Detect Lines and Curves in Pictures, Technical Note 36, Artificial Intelligence Center, SRI International .

[11]

N. Kiryati, Y. Eldar, A. M. Bruckstein (1991) A Probabilistic Hough Transform, Pattern Recognition . 24 (4):303-316.

Digital Library

[12]

J. Illingworth, J. Kittler (1988) A Survey on the Hough Transform, Computer Vision, Graphics, and Image Processing . 44 :87-116.

Digital Library

[13]

H. Kälviäinen, P. Hirvonen, L. Xu, E. Oja (1995) Probabilistic and Non-Probabilistic Hough Transforms: Overview and Comparisons, Image and Vision Computing . 13 (4).

[14]

A. Ylä-Jääski, N. Kiryati (1994) Adaptive Termination of Voting in the Probabilistic Circular Hough Transform, IEEE Transactions on Pattern Analysis and Machine Intelligence . 16 (9).

Digital Library

[15]

J. Matas, C. Galambos, J. Kittler (1998) Progressive Probabilistic Hough Transform, In Proceedings of the British Machine Vision Conference . 1 :256-265.

[16]

L. Xu, E. Oja, P. Kultanen (1990) A new Curve DetectionMethod: Randomized Hough Transform (RHT), Pattern Recognition Letters . 11 :331-338.

Digital Library

[17]

A. Censi, S. Carpin (2009) HSM3D: Feature-Less Global 6DOF Scan-Matching in the Hough/Radon Domain, In Proceedings of the IEEE International Conference on Robotics and Automation .

Digital Library

[18]

T. Zaharia, F. Preteux (2002) Shape-based Retrieval of 3D Mesh Models, In Proceedings of the IEEE International Conference on Multimedia and Expo .

[19]

D. Borrmann, J. Elseberg (2009) Deforming Scans for Improving the Map Quality Using Plane Extraction and Thin Plate Splines, Master thesis, University of Osnabrück, Germany .

[20]

F. Tarsha-Kurdi, T. Landes, P. Grussenmeyer (2007) Hough-transform and extended RANSAC algorithms for automatic detection of 3d building roof planes from lidar data, IAPRS . 36 :Part 3 / W52.

[21]

M. B. Dillencourt, H. Samet, T. Tamminen (1992) A general approach to connected-component labeling for arbitrary image representations, J. ACM . 39 :253-280.

Digital Library

[22]

Environments by Means of 3D Perception, In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '04). New Orleans, USA . 4204-4209.

Cited By

Romanengo CRaffo ABiasotti SFalcidieno B(2023)Recognizing geometric primitives in 3D point clouds of mechanical CAD objectsComputer-Aided Design10.1016/j.cad.2023.103479157:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.cad.2023.103479
Daghigh HTannant DDaghigh VLichti DLindenbergh R(2022)A critical review of discontinuity plane extraction from 3D point cloud data of rock mass surfacesComputers & Geosciences10.1016/j.cageo.2022.105241169:COnline publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1016/j.cageo.2022.105241
Xiao ZGao JWu DZhang LZhang Q(2022)Fast plane extraction method based on the point pair featureMultimedia Tools and Applications10.1007/s11042-022-14063-982:10(15027-15042)Online publication date: 27-Oct-2022
https://dl.acm.org/doi/10.1007/s11042-022-14063-9
Show More Cited By

Recommendations

Continuous plane detection in point-cloud data based on 3D Hough Transform

We propose a 3D Hough Transform plane detector for depth sensors.Several significant optimizations are proposed to maximize its practical usability.Continuous flow of frames is used to accumulate and iteratively refine detected planes.Comparison with ...
N-Point Hough transform for line detection

In this paper, we introduce the N-point Hough transform for the detection of a large number of planar lines in a noisy image. The N-point Hough transform yields the randomized Hough transform and the three-point Hough transform if we set N=2 and N=3, ...
Advanced hough transform using a multilayer fractional fourier method

The Hough transform (HT) is a commonly used technique for the identification of straight lines in an image. The Hough transform can be equivalently computed using the Radon transform (RT), by performing line detection in the frequency domain through use ...

Comments

Information & Contributors

Information

Published In

cover image 3D Research

3D Research Volume 2, Issue 2

March 2011

45 pages

ISSN:2092-6731

Issue’s Table of Contents

Copyright © Copyright © 2011 3D Display Research Center and Springer-Verlag Berlin Heidelberg.

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 March 2011

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

30
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 07 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Romanengo CRaffo ABiasotti SFalcidieno B(2023)Recognizing geometric primitives in 3D point clouds of mechanical CAD objectsComputer-Aided Design10.1016/j.cad.2023.103479157:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.cad.2023.103479
Daghigh HTannant DDaghigh VLichti DLindenbergh R(2022)A critical review of discontinuity plane extraction from 3D point cloud data of rock mass surfacesComputers & Geosciences10.1016/j.cageo.2022.105241169:COnline publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1016/j.cageo.2022.105241
Xiao ZGao JWu DZhang LZhang Q(2022)Fast plane extraction method based on the point pair featureMultimedia Tools and Applications10.1007/s11042-022-14063-982:10(15027-15042)Online publication date: 27-Oct-2022
https://dl.acm.org/doi/10.1007/s11042-022-14063-9
Kerautret BKrähenbühl ADebled-Rennesson ILachaud J(2022)3D Geometric Analysis of Tubular Objects Based on Surface Normal AccumulationImage Analysis and Processing — ICIAP 201510.1007/978-3-319-23231-7_29(319-331)Online publication date: 10-Mar-2022
https://dl.acm.org/doi/10.1007/978-3-319-23231-7_29
Pryor WLin YBerenson D(2021)Integrated affordance detection and humanoid locomotion planning2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids)10.1109/HUMANOIDS.2016.7803264(125-132)Online publication date: 10-Mar-2021
https://dl.acm.org/doi/10.1109/HUMANOIDS.2016.7803264
Hu LXiao JWang Y(2020)Efficient and automatic plane detection approach for 3-D rock mass point cloudsMultimedia Tools and Applications10.1007/s11042-019-08189-679:1-2(839-864)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1007/s11042-019-08189-6
de Souza RSierra-Franco CSantos PPolonia Rios Mde Mattos Nascimento DBarbosa Raposo A(2020)Automatic Deformation Detection and Analysis Visualization of 3D Steel Structures in As-Built Point CloudsHuman-Computer Interaction. Design and User Experience10.1007/978-3-030-49059-1_47(635-654)Online publication date: 19-Jul-2020
https://dl.acm.org/doi/10.1007/978-3-030-49059-1_47
Jin ZTillo TZou WZhao YLi X(2019)Robust Plane Detection Using Depth Information From a Consumer Depth CameraIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2017.278018129:2(447-460)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1109/TCSVT.2017.2780181
Paudel DHabed ADemonceaux CVasseur P(2019)Robust and Optimal Registration of Image Sets and Structured Scenes via Sum-of-Squares PolynomialsInternational Journal of Computer Vision10.1007/s11263-018-1114-2127:5(415-436)Online publication date: 1-May-2019
https://dl.acm.org/doi/10.1007/s11263-018-1114-2
Grant WVoorhies RItti L(2019)Efficient Velodyne SLAM with point and plane featuresAutonomous Robots10.1007/s10514-018-9794-643:5(1207-1224)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1007/s10514-018-9794-6
Show More Cited By

View Options

View options

Figures

Tables

Media

View Issue’s Table of Contents