Keywords
3D reconstruction, LIDAR
Abstract
As more data sources have become abundantly available, an increased interest in 3D reconstruction has emerged in the image processing academic community. Applications for 3D reconstruction of urban and residential buildings consist of urban planning, network planning for mobile communication, tourism information systems, spatial analysis of air pollution and noise nuisance, microclimate investigations, and Geographical Information Systems (GISs). Previous, classical, 3D reconstruction algorithms solely utilized aerial photography. With the advent of LIDAR systems, current algorithms explore using captured LIDAR data as an additional feasible source of information for 3D reconstruction. Preprocessing techniques are proposed for the development of an autonomous 3D Reconstruction algorithm. The algorithm is designed for autonomously deriving three dimensional models of urban and residential buildings from raw LIDAR data. First, a greedy insertion triangulation algorithm, modified with a proposed noise filtering technique, triangulates the raw LIDAR data. The normal vectors of those triangles are then passed to an unsupervised clustering algorithm – Fuzzy Simplified Adaptive Resonance Theory (Fuzzy SART). Fuzzy SART returns a rough grouping of coplanar triangles. A proposed multiple regression algorithm then further refines the coplanar grouping by further removing outliers and deriving an improved planar segmentation of the raw LIDAR data. Finally, further refinement is achieved by calculating the intersection of the best fit roof planes and moving nearby points close to that intersection to exist at the intersection, resulting in straight roof ridges. The end result of the aforementioned techniques culminates in a well defined model approximating the considered building depicted by the LIDAR data.
Notes
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Graduation Date
2006
Semester
Summer
Advisor
Kasparis, Takis
Degree
Master of Science in Electrical Engineering (M.S.E.E.)
College
College of Engineering and Computer Science
Department
Electrical Engineering and Computer Science
Degree Program
Electrical Engineering
Format
application/pdf
Identifier
CFE0001315
URL
http://purl.fcla.edu/fcla/etd/CFE0001315
Language
English
Length of Campus-only Access
None
Access Status
Masters Thesis (Open Access)
STARS Citation
Shorter, Nicholas, "Heuristic 3d Reconstruction Of Irregular Spaced Lidar" (2006). Electronic Theses and Dissertations. 4468.
https://stars.library.ucf.edu/etd/4468