Language:
English
繁體中文
Help
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Locally Adaptive Stereo Vision Based...
~
ProQuest Information and Learning Co.
Locally Adaptive Stereo Vision Based 3D Visual Reconstruction.
Record Type:
Language materials, manuscript : Monograph/item
Title/Author:
Locally Adaptive Stereo Vision Based 3D Visual Reconstruction./
Author:
Li, Jinjin.
Description:
1 online resource (128 pages)
Notes:
Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
Contained By:
Dissertation Abstracts International78-10B(E).
Subject:
Electrical engineering. -
Online resource:
click for full text (PQDT)
ISBN:
9781369761412
Locally Adaptive Stereo Vision Based 3D Visual Reconstruction.
Li, Jinjin.
Locally Adaptive Stereo Vision Based 3D Visual Reconstruction.
- 1 online resource (128 pages)
Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
Thesis (Ph.D.)--Arizona State University, 2017.
Includes bibliographical references
Using stereo vision for 3D reconstruction and depth estimation has become a popular and promising research area as it has a simple setup with passive cameras and relatively efficient processing procedure. The work in this dissertation focuses on locally adaptive stereo vision methods and applications to different imaging setups and image scenes.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9781369761412Subjects--Topical Terms:
596380
Electrical engineering.
Index Terms--Genre/Form:
554714
Electronic books.
Locally Adaptive Stereo Vision Based 3D Visual Reconstruction.
LDR
:03655ntm a2200373Ki 4500
001
919572
005
20181129115238.5
006
m o u
007
cr mn||||a|a||
008
190606s2017 xx obm 000 0 eng d
020
$a
9781369761412
035
$a
(MiAaPQ)AAI10275741
035
$a
(MiAaPQ)asu:17017
035
$a
AAI10275741
040
$a
MiAaPQ
$b
eng
$c
MiAaPQ
$d
NTU
100
1
$a
Li, Jinjin.
$3
1194182
245
1 0
$a
Locally Adaptive Stereo Vision Based 3D Visual Reconstruction.
264
0
$c
2017
300
$a
1 online resource (128 pages)
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
500
$a
Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
500
$a
Adviser: Lina Karam.
502
$a
Thesis (Ph.D.)--Arizona State University, 2017.
504
$a
Includes bibliographical references
520
$a
Using stereo vision for 3D reconstruction and depth estimation has become a popular and promising research area as it has a simple setup with passive cameras and relatively efficient processing procedure. The work in this dissertation focuses on locally adaptive stereo vision methods and applications to different imaging setups and image scenes.
520
$a
Solder ball height and substrate coplanarity inspection is essential to the detection of potential connectivity issues in semi-conductor units. Current ball height and substrate coplanarity inspection tools are expensive and slow, which makes them difficult to use in a real-time manufacturing setting. In this dissertation, an automatic, stereo vision based, in-line ball height and coplanarity inspection method is presented. The proposed method includes an imaging setup together with a computer vision algorithm for reliable, in-line ball height measurement. The imaging setup and calibration, ball height estimation and substrate coplanarity calculation are presented with novel stereo vision methods. The results of the proposed method are evaluated in a measurement capability analysis (MCA) procedure and compared with the ground-truth obtained by an existing laser scanning tool and an existing confocal inspection tool. The proposed system outperforms existing inspection tools in terms of accuracy and stability.
520
$a
In a rectified stereo vision system, stereo matching methods can be categorized into global methods and local methods. Local stereo methods are more suitable for real-time processing purposes with competitive accuracy as compared with global methods. This work proposes a stereo matching method based on sparse locally adaptive cost aggregation. In order to reduce outlier disparity values that correspond to mis-matches, a novel sparse disparity subset selection method is proposed by assigning a significance status to candidate disparity values, and selecting the significant disparity values adaptively. An adaptive guided filtering method using the disparity subset for refined cost aggregation and disparity calculation is demonstrated. The proposed stereo matching algorithm is tested on the Middlebury and the KITTI stereo evaluation benchmark images. A performance analysis of the proposed method in terms of the I0 norm of the disparity subset is presented to demonstrate the achieved efficiency and accuracy.
533
$a
Electronic reproduction.
$b
Ann Arbor, Mich. :
$c
ProQuest,
$d
2018
538
$a
Mode of access: World Wide Web
650
4
$a
Electrical engineering.
$3
596380
650
4
$a
Computer science.
$3
573171
650
4
$a
Artificial intelligence.
$3
559380
655
7
$a
Electronic books.
$2
local
$3
554714
690
$a
0544
690
$a
0984
690
$a
0800
710
2
$a
ProQuest Information and Learning Co.
$3
1178819
710
2
$a
Arizona State University.
$b
Electrical Engineering.
$3
845389
773
0
$t
Dissertation Abstracts International
$g
78-10B(E).
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10275741
$z
click for full text (PQDT)
based on 0 review(s)
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login