Phd Position F/m 3D Computer Vision and Geometry - Sophia Antipolis, France - Inria

Inria

Entreprise vérifiée

Sophia Antipolis, France

il y a 1 semaine

Posté par:

Sophie Dupont

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Description

Le descriptif de l'offre ci-dessous est en Anglais_

Type de contrat :

CDD

Niveau de diplôme exigé :
Bac + 5 ou équivalent

Fonction :
Doctorant

A propos du centre ou de la direction fonctionnelle:
The Inria centre at Université Côte d'Azur includes 37 research teams and 8 support services. The centre's staff (about 500 people) is made up of scientists of different nationalities, engineers, technicians and administrative staff.

The teams are mainly located on the university campuses of Sophia Antipolis and Nice as well as Montpellier, in close collaboration with research and higher education laboratories and establishments (Université Côte d'Azur, CNRS, INRAE, INSERM...), but also with the regiona economic players.

With a presence in the fields of computational neuroscience and biology, data science and modeling, software engineering and certification, as well as collaborative robotics, the Inria Centre at Université Côte d'Azur is a major player in terms of scientific excellence through its results and collaborations at both European and international levels.

Mission confiée:

Efficient data structures and algorithms for processing massive point clouds

Context
Analyzing 3D point clouds captured from real-world environments is a core component of Geometry. Processing and 3D Computer Vision.

Processing tasks include, for instance, the estimation of local geometric properties, semantic segmentation, extraction of geometric primitives or reconstruction into surface meshes.

Algorithms that perform these tasks are typically designed to handle up to a few million points efficiently [1,2].

With the technological advances on sensors and storage capacity, new acquisition protocols generate more and more massive point clouds that contain billions of points.

The naive solution then consists in decomposing the space into blocks of reasonable number of points before performing parallel computing.

This solution is however prone to border effect errors and does not allow the analyze of point clouds at global scales.

Moreover, it requires high computing resources and storage capacity.

Objectives

The goal of this PhD is to (i) investigate new data structures to read, compress and store the information contained in massive point clouds efficiently, and (ii) to rethink popular processing tasks so that they can operate at multiple scales directly from such data structures.

Keywords
Geometry processing, 3D computer vision, massive point clouds, point set processing, geometric data structures

References
[1] The CGAL Project. CGAL User and Reference Manual. CGAL Editorial Board, 5.5.1 edition, 2022.
[2] CloudCompare, version 2.10.3, 2022.
[3] Pajarola. Stream-Processing Points. IEEE Visualization 2005
[4] Zhou and Neumann. A streaming framework for seamless building reconstruction from large-scale aerial lidar data. CVPR 2009
[5] Mostegel, Prettenthaler, Fraundorfer and Bischof. Scalable Surface Reconstruction from Point Clouds with Extreme Scale and Density Diversity. CVPR 2017
[6] Schütz, Ohrhallinger, Wimmer. Fast Out-of-Core Octree Generation for Massive Point Clouds. Computer Graphics
Forum, vol 39(7), 2020
[7] Elseberg, borrmann and Nuchter. One billion points in the cloud - an octree for efficient processing of 3D laser scans. ISPRS Journal of Photogrammetry and Remote Sensing, vol 76, 2013
[8] Fang, Lafarge, and Desbrun. Shape detection at structural scales. CVPR 2018
[9] Landrieu and Simonovsky. Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs. CVPR 2018
[10] Potamias, Bouritsas and Zafeiriou.

Revisiting Point Cloud Simplification :
A Learnable Feature Preserving Approach. ECCV 2022

Compétences:

program in C/C++ and Python, be fluent in English, and be creative and rigorous.

Avantages:

Subsidized meals
Partial reimbursement of public transport costs
Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
Professional equipment available (videoconferencing, loan of computer equipment, etc.)
Social, cultural and sports events and activities
Access to vocational training
Social security coverage

Rémunération:

Duration: 36 months

Location:
Sophia Antipolis, France

Gross Salary per month: 2100€ brut per month (year 1 & 2) and 2190€ brut per month (year 3)

Informations générales:

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Thème/Domaine: Interaction et visualisation

Calcul Scientifique (BAP E)

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Ville: Sophia Antipolis

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Centre Inria: Centre Inria d'Université Côte d'Azur
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Date de prise de fonction souhaitée:
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Durée de contrat: 3 ans
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Date limite pour postuler:

Consignes pour postuler:

Sécurité défense:

Ce poste est susceptible d'être affecté dans une zone à régime r