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Theses

Multi-scale Point Cloud Analysis

Thibault Lejemble 1
1 IRIT-STORM - Structural Models and Tools in Computer Graphics
IRIT - Institut de recherche en informatique de Toulouse
Abstract : 3D acquisition techniques like photogrammetry and laser scanning are commonly used in numerous fields such as reverse engineering, archeology, robotics and urban planning. The main objective is to get virtual versions of real objects in order to visualize, analyze and process them easily. Acquisition techniques become more and more powerful and affordable which creates important needs to process efficiently the resulting various and massive 3D data. Data are usually obtained in the form of unstructured 3D point cloud sampling the scanned surface. Traditional signal processing methods cannot be directly applied due to the lack of spatial parametrization. Points are only represented by their 3D coordinates without any particular order. This thesis focuses on the notion of scale of analysis defined by the size of the neighborhood used to locally characterize the point-sampled surface. The analysis at different scales enables to consider various shapes which increases the analysis pertinence and the robustness to acquired data imperfections. We first present some theoretical and practical results on curvature estimation adapted to a multi-scale and multi-resolution representation of point clouds. They are used to develop multi-scale algorithms for the recognition of planar and anisotropic shapes such as cylinders and feature curves. Finally, we propose to compute a global 2D parametrization of the underlying surface directly from the 3D unstructured point cloud.
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  • HAL Id : tel-03170824, version 1

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Thibault Lejemble. Multi-scale Point Cloud Analysis. Computer Vision and Pattern Recognition [cs.CV]. Université Paul Sabatier - Toulouse III, 2020. English. ⟨NNT : 2020TOU30184⟩. ⟨tel-03170824⟩

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