Improving robustness of 3D reconstruction for sparse captures and challenging environments

The applications of 3D modeling in the world are ubiquitous. For example, the construction industry models ongoing projects to monitor progress. The housing industry uses 360 images to develop 3D floor plans to help customers visualize home interiors. These applications rely on real-world data that poses challenges for 3D modeling systems. In this dissertation, I will discuss the specific challenges that arise during the modeling process, and how we address them. First, images capture the scene of interest, which can be onerous as planned capture paths can result in reconstruction failures or yield incomplete models. Our feature track simulator uses a camera trajectory and scene geometry to evaluate planned paths prior to the collection process. Next, a structure from motion (SfM) system reconstructs the scene, and outputs camera parameters and image poses. Images that contain repeated or duplicate structures present ambiguities and can cause catastrophic failures in reconstruction. Our approach discounts matches on repeated structures and estimates correct poses using a set of reliable images in the resectioning process. Then, a multi-view stereo (MVS) system uses the camera parameters and image poses to generate a dense model. MVS systems require sufficient overlap between images for accurate depth estimation, which is often burdensome and costly. Our solution detects and completes planar surfaces with only one or two views, and circumvents the overlap requirement.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2023

Author dc:creator

• Kataria, Raj

Contributors dc:contributor

• Hoiem, Derek
• Golparvar-Fard, Mani
• Forsyth, David
• Furukawa, Yasutaka

• Structure From Motion
• Sfm
• Multi-view Stereo
• Mvs
• 3d Vision

Statement dc:rights

• Copyright 2023 Raj Kataria

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/120235

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F120235