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Image-based Urban Modeling
The Hong Kong University of Science and Technology
Department of Computer Science and Engineering
PhD Thesis Defence
Title: "Image-based Urban Modeling"
By
Mr. Tian FANG
Abstract
Nowadays, there are high demands on 3D modeling of urban environments. In
urban areas, buildings and trees greatly affect the landscape of urban
areas. How to reconstruct 3D models for buildings and trees is an
important problem for urban modeling. The large number of buildings and
trees requires cheaper and more automatic approaches to be developed.
Traditional scanner-based approaches require expensive equipment and can
only capture unstructured 3D points without photometric appearance of the
scenes, while manual editing approaches require lots of man-power. Here,
image-based modeling which can reconstruct the mathematical 3D
representation of objects from images with registered color texture map
provides a tempting solution.
In contrast to traditional image-based building modeling that relies on
general smoothness assumption of the reconstructed surface to automatic
recover irregular surface meshes or requires fully manual editing to build
up the correspondence among images to generate a regularized surface
representation, in this thesis, we target to create regularized 3D facade
models with less user interactions. We propose methods to improve the key
aspects of existing work flow. First, a resampling scheme is proposed to
select dominant correspondences which yield a good result for large scale
quasi-dense reconstruction as if all correspondences are involved. Then,
to model single facade, we propose a concept of unwrappable facades which
generalizes the traditional concept of elevations to unwrappable surface.
This representation enables us to model larger range of facades with a
global shape description semi-automatically than previous methods do. This
representation further makes adding detailed decorations more easily and
image-based facade synthesis possible. Finally, we present a façade
partition scheme that use the natural vertical lines on the building to
automatically separate a large number of urban images and 3D point clouds
into the granularity of facade level. Automatic image-based facade
modeling becomes possible with our partition scheme.
To overcome the drawbacks of existing image-based tree modeling
techniques, e.g. lacks of complete multiple view data and tedious user
interaction on preprocessing, we describe a system to model a tree with
single image. Given a near orthogonal image of a tree, as few as two
strokes, one for marking a visible branch and the other for marking the
tree crown, are required to model a photo-realistic tree. The marked
visible branches are used to guide a branch tracing algorithm to extract
remaining visible branches automatically. The extracted visible branches
are used to construct a branch library which is later grown using a
non-parametric growing algorithm under the constraint of the extracted
tree crown. We also demonstrate that additional information from multiple
view images and laser scanner can be used to further eliminate this user
interaction with the help of joint segmentation and analysis.
Date: Friday, 5 August 2011
Time: 2:00pm – 4:00pm
Venue: Room 3584
Lifts 27/28
Chairman: Prof. Yang Leng (MECH)
Committee Members: Prof. Long Quan (Supervisor)
Prof. Huamin Qu
Prof. Chiew-Lan Tai
Prof. Kai Tang (MECH)
Prof. Shing-Chow Chan (Elec. & Elec. Engg., HKU)
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