Geometric modeling of indoor scenes from acquired point data

Sven Oesau 1
1 TITANE - Geometric Modeling of 3D Environments
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : Geometric modeling and semantization of indoor scenes from sampled point data is an emerging research topic. Recent advances in acquisition technologies provide highly accurate laser scanners and low-cost handheld RGB-D cameras for real-time acquisition. However, the processing of large data sets is hampered by high amounts of clutter and various defects such as missing data, outliers and anisotropic sampling. This thesis investigates three novel methods for efficient geometric modeling and semantization from unstructured point data: Shape detection, classification and geometric modeling. Chapter 2 introduces two methods for abstracting the input point data with primitive shapes. First, we propose a line extraction method to detect wall segments from a horizontal cross-section of the input point cloud. Second, we introduce a region growing method that progressively detects and reinforces regularities of planar shapes. This method utilizes regularities common to man-made architecture, i.e. coplanarity, parallelism and orthogonality, to reduce complexity and improve data fitting in defect-laden data. Chapter 3 introduces a method based on statistical analysis for separating clutter from structure. We also contribute a supervised machine learning method for object classification based on sets of planar shapes. Chapter 4 introduces a method for 3D geometric modeling of indoor scenes. We first partition the space using primitive shapes detected from permanent structures. An energy formulation is then used to solve an inside/outside labeling of a space partitioning, the latter providing robustness to missing data and outliers.
Document type :
Theses
Liste complète des métadonnées

Cited literature [71 references]  Display  Hide  Download

https://tel.archives-ouvertes.fr/tel-01176721
Contributor : Abes Star <>
Submitted on : Wednesday, July 15, 2015 - 5:17:05 PM
Last modification on : Wednesday, September 26, 2018 - 3:25:23 AM
Document(s) archivé(s) le : Friday, October 16, 2015 - 11:50:26 AM

File

2015NICE4034.pdf
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-01176721, version 1

Collections

Citation

Sven Oesau. Geometric modeling of indoor scenes from acquired point data. Other [cs.OH]. Université Nice Sophia Antipolis, 2015. English. ⟨NNT : 2015NICE4034⟩. ⟨tel-01176721⟩

Share

Metrics

Record views

1078

Files downloads

1312