An approach to generate geometric models from multiple range images

The research described in this dissertation focuses on the development of a new approach for the generation of geometric models from multiple-view range image data. Through intensive comparison and evaluation of different representations, the cross-section contour based representation is conclude...

Full description

Bibliographic Details
Main Author: Yao, Helai
Other Authors: Podhorodeski, Ronald Peter
Format: Others
Language:English
en
Published: 2018
Subjects:
Online Access:https://dspace.library.uvic.ca//handle/1828/9748
id ndltd-uvic.ca-oai-dspace.library.uvic.ca-1828-9748
record_format oai_dc
spelling ndltd-uvic.ca-oai-dspace.library.uvic.ca-1828-97482018-07-20T17:18:12Z An approach to generate geometric models from multiple range images Yao, Helai Podhorodeski, Ronald Peter Dong, Zuomin Imaging systems Scanning systems Image processing The research described in this dissertation focuses on the development of a new approach for the generation of geometric models from multiple-view range image data. Through intensive comparison and evaluation of different representations, the cross-section contour based representation is concluded to be ideal for modeling with range image data. The representation is shown to be at an intermediate level - compatible with both the low-level of range image data and with the need to provide relatively high-level geometric and topological information in models. A new concept of generating partial models within device frames, frames associated with the working principle and geometry of a range sensor, is introduced. The range data are well distributed in the device frame. This good data distribution facilitates computations relevant to rendering the cross-sections required by the representation and relevent to identifying occlusions present in the image. Methodology for merging the partial models with a current global model is developed to allow the incorporation of redundancy between the partial model and the current global model and to allow growth of the global model. A simulation of the ERIM imaging-radar based range sensor, a prototype triangulation-based range sensor developed for this research and a commercial HYMARC range sensing system are used for approach verification. The device frames associated with the sensors are derived, and used to test the modeling approaches and the developed system. The presented research: demonstrates the suitability of the cross-section based representation for range-image based modeling systems; introduces a new concept and associated methods for generating cross-section contour models in range sensor device frames to take advantage of well distributed data; develops a series of algorithms for partial modeling in the device frame and for global model integration; and demonstrates the feasibility of the developed new approaches for applications by testing the system for multiple sensor types. Graduate 2018-07-19T21:34:15Z 2018-07-19T21:34:15Z 1996 2018-07-19 Thesis https://dspace.library.uvic.ca//handle/1828/9748 English en Available to the World Wide Web application/pdf
collection NDLTD
language English
en
format Others
sources NDLTD
topic Imaging systems
Scanning systems
Image processing
spellingShingle Imaging systems
Scanning systems
Image processing
Yao, Helai
An approach to generate geometric models from multiple range images
description The research described in this dissertation focuses on the development of a new approach for the generation of geometric models from multiple-view range image data. Through intensive comparison and evaluation of different representations, the cross-section contour based representation is concluded to be ideal for modeling with range image data. The representation is shown to be at an intermediate level - compatible with both the low-level of range image data and with the need to provide relatively high-level geometric and topological information in models. A new concept of generating partial models within device frames, frames associated with the working principle and geometry of a range sensor, is introduced. The range data are well distributed in the device frame. This good data distribution facilitates computations relevant to rendering the cross-sections required by the representation and relevent to identifying occlusions present in the image. Methodology for merging the partial models with a current global model is developed to allow the incorporation of redundancy between the partial model and the current global model and to allow growth of the global model. A simulation of the ERIM imaging-radar based range sensor, a prototype triangulation-based range sensor developed for this research and a commercial HYMARC range sensing system are used for approach verification. The device frames associated with the sensors are derived, and used to test the modeling approaches and the developed system. The presented research: demonstrates the suitability of the cross-section based representation for range-image based modeling systems; introduces a new concept and associated methods for generating cross-section contour models in range sensor device frames to take advantage of well distributed data; develops a series of algorithms for partial modeling in the device frame and for global model integration; and demonstrates the feasibility of the developed new approaches for applications by testing the system for multiple sensor types. === Graduate
author2 Podhorodeski, Ronald Peter
author_facet Podhorodeski, Ronald Peter
Yao, Helai
author Yao, Helai
author_sort Yao, Helai
title An approach to generate geometric models from multiple range images
title_short An approach to generate geometric models from multiple range images
title_full An approach to generate geometric models from multiple range images
title_fullStr An approach to generate geometric models from multiple range images
title_full_unstemmed An approach to generate geometric models from multiple range images
title_sort approach to generate geometric models from multiple range images
publishDate 2018
url https://dspace.library.uvic.ca//handle/1828/9748
work_keys_str_mv AT yaohelai anapproachtogenerategeometricmodelsfrommultiplerangeimages
AT yaohelai approachtogenerategeometricmodelsfrommultiplerangeimages
_version_ 1718713679902408704