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63627

A Survey of RANSAC enhancements for Plane Detection in 3D Point Clouds

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Last updated: 25 Dec 2024

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Abstract

Planar surfaces are distinguished features of man-made environment, which are used in many computer vision applications such as object detection, motion segmentation, 3D scene reconstruction, and 3D mapping. One of the most used technique for robust plane detection is the RANdom SAmple Consensus (RANSAC), which is a global iterative method for estimating the parameters of a certain model from input data points contaminated by a set of outliers (noisy data). Unfortunately, the standard RANSAC suffers from some problems regarding the processing time, accuracy of fitting data, and finding an optimal solution. This paper gives a review study of the most recent RANSAC enhancements techniques. In addition, it covers the solving techniques for the speed, accuracy and optimality problems.

DOI

10.21608/mjeer.2017.63627

Authors

First Name

Ramy Ashraf

Last Name

Zeineldin

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Affiliation

Dept. of Computer Science and Eng., Faculty of Elect., Eng., Menoufia University, Menouf, Egypt.

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First Name

Nawal Ahmed

Last Name

El-Fishawy

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Affiliation

Dept. of Computer Science and Eng., Faculty of Elect., Eng., Menoufia University, Menouf, Egypt.

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Volume

26

Article Issue

2

Related Issue

9503

Issue Date

2017-07-01

Receive Date

2017-03-09

Publish Date

2017-07-01

Page Start

519

Page End

537

Print ISSN

1687-1189

Online ISSN

2682-3535

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https://mjeer.journals.ekb.eg/article_63627.html

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https://mjeer.journals.ekb.eg/service?article_code=63627

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13

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Original Article

Type Code

1,088

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Journal

Publication Title

Menoufia Journal of Electronic Engineering Research

Publication Link

https://mjeer.journals.ekb.eg/

MainTitle

A Survey of RANSAC enhancements for Plane Detection in 3D Point Clouds

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Article

Created At

22 Jan 2023