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Rafael Grompone von Gioi

Researcher at Université Paris-Saclay

Publications -  62
Citations -  1518

Rafael Grompone von Gioi is an academic researcher from Université Paris-Saclay. The author has contributed to research in topics: Computer science & Line segment. The author has an hindex of 12, co-authored 50 publications receiving 1219 citations. Previous affiliations of Rafael Grompone von Gioi include École normale supérieure de Cachan & École Normale Supérieure.

Papers
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Journal ArticleDOI

LSD: a Line Segment Detector

TL;DR: LSD is a linear-time Line Segment Detector giving subpixel accurate results and uses an a contrario validation approach according to Desolneux, Moisan, and Morel’s theory.
Book ChapterDOI

A Parameterless Line Segment and Elliptical Arc Detector with Enhanced Ellipse Fitting

TL;DR: A combined line segment and elliptical arc detector, which formally guarantees the control of the number of false positives and requires no parameter tuning, is proposed.
Proceedings ArticleDOI

Finding Vanishing Points via Point Alignments in Image Primal and Dual Domains

TL;DR: A novel method for automatic vanishing point detection based on primal and dual point alignment detection with the use of the recently introduced PClines dual spaces and a robust point alignment detector leads to a very accurate algorithm.
Journal ArticleDOI

On Straight Line Segment Detection

TL;DR: A comprehensive method for detecting straight line segments in any digital image, accurately controlling both false positive and false negative detections is proposed, based on Helmholtz principle.
Journal ArticleDOI

A Precision Analysis of Camera Distortion Models

TL;DR: This paper addresses the question of identifying the right camera direct or inverse distortion model, permitting a high subpixel precision to fit to real camera distortion, and concluded that, although high degree polynomials were required to reach a high precision of 1/100 pixels, such polynmials were easily estimated and produced a precise distortion modeling without overfitting.