Language:
English
繁體中文
Help
回圖書館首頁
手機版館藏查詢
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Stereo-Based Three-Dimensional Model...
~
Yu, Ting.
Linked to FindBook
Google Book
Amazon
博客來
Stereo-Based Three-Dimensional Model Acquisition and Motion Detection.
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Stereo-Based Three-Dimensional Model Acquisition and Motion Detection./
Author:
Yu, Ting.
Description:
98 p.
Notes:
Source: Masters Abstracts International, Volume: 49-06, page: .
Contained By:
Masters Abstracts International49-06.
Subject:
Computer Science. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR74199
ISBN:
9780494741993
Stereo-Based Three-Dimensional Model Acquisition and Motion Detection.
Yu, Ting.
Stereo-Based Three-Dimensional Model Acquisition and Motion Detection.
- 98 p.
Source: Masters Abstracts International, Volume: 49-06, page: .
Thesis (M.C.S.)--University of Ottawa (Canada), 2010.
Deformable models have a long tradition in computer graphics and computer vision. This thesis looks at the capture of surface deformation based on stereo vision. In recent years, 3D reconstruction and motion detection has attracted great attention. In this thesis a framework for 3D reconstruction from mutli-view images followed by isometry-based motion detection is proposed. For 3D reconstruction, the thesis proposes a multi-view stereo algorithm based on well-known window-based matching combined with fusion of multiple matching results. To improve the matching result, some low-level image processing algorithms, camera calibration and background detection are utilized. For window-based matching, a new hybrid matching method is introduced by combining both, a measure of intensity difference and intensity distribution difference. Multiple MVS pointclouds from different reference views are fused with two new fusion strategies to generate a better final reconstruction. To characterize the performance of our matching method and fusion strategies, an evaluation based on the quality of reconstruction is given in the thesis. Based on 3D pointclouds of object surface obtained with stereo, the deformation of the surface is captured. To generate dense motion vectors over a deformed surface, a simple window-based 3D flow method is applied by using isometry of the observed surface as its primary matching constraint. The method uses feature points as anchoring references of the surface deformation. Given a set of matched features no other intensity information is used and hence the method can tolerate intensity changes over time. The approach is shown to work well on two example scenes which capture non-rigid isometric and general deformations. The thesis also presents experiments demonstrating the stability of the geodesic approximation employed in the isometry-based matching when the 3D pointclouds are sparse.
ISBN: 9780494741993Subjects--Topical Terms:
626642
Computer Science.
Stereo-Based Three-Dimensional Model Acquisition and Motion Detection.
LDR
:02688nam 2200241 4500
001
1401567
005
20111020092038.5
008
130515s2010 ||||||||||||||||| ||eng d
020
$a
9780494741993
035
$a
(UMI)AAIMR74199
035
$a
AAIMR74199
040
$a
UMI
$c
UMI
100
1
$a
Yu, Ting.
$3
1680713
245
1 0
$a
Stereo-Based Three-Dimensional Model Acquisition and Motion Detection.
300
$a
98 p.
500
$a
Source: Masters Abstracts International, Volume: 49-06, page: .
502
$a
Thesis (M.C.S.)--University of Ottawa (Canada), 2010.
520
$a
Deformable models have a long tradition in computer graphics and computer vision. This thesis looks at the capture of surface deformation based on stereo vision. In recent years, 3D reconstruction and motion detection has attracted great attention. In this thesis a framework for 3D reconstruction from mutli-view images followed by isometry-based motion detection is proposed. For 3D reconstruction, the thesis proposes a multi-view stereo algorithm based on well-known window-based matching combined with fusion of multiple matching results. To improve the matching result, some low-level image processing algorithms, camera calibration and background detection are utilized. For window-based matching, a new hybrid matching method is introduced by combining both, a measure of intensity difference and intensity distribution difference. Multiple MVS pointclouds from different reference views are fused with two new fusion strategies to generate a better final reconstruction. To characterize the performance of our matching method and fusion strategies, an evaluation based on the quality of reconstruction is given in the thesis. Based on 3D pointclouds of object surface obtained with stereo, the deformation of the surface is captured. To generate dense motion vectors over a deformed surface, a simple window-based 3D flow method is applied by using isometry of the observed surface as its primary matching constraint. The method uses feature points as anchoring references of the surface deformation. Given a set of matched features no other intensity information is used and hence the method can tolerate intensity changes over time. The approach is shown to work well on two example scenes which capture non-rigid isometric and general deformations. The thesis also presents experiments demonstrating the stability of the geodesic approximation employed in the isometry-based matching when the 3D pointclouds are sparse.
590
$a
School code: 0918.
650
4
$a
Computer Science.
$3
626642
690
$a
0984
710
2
$a
University of Ottawa (Canada).
$3
1017488
773
0
$t
Masters Abstracts International
$g
49-06.
790
$a
0918
791
$a
M.C.S.
792
$a
2010
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR74199
based on 0 review(s)
Location:
ALL
電子資源
Year:
Volume Number:
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
W9164706
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login