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
Methods for faster feature matching ...
~
Treen, Geoffrey.
Linked to FindBook
Google Book
Amazon
博客來
Methods for faster feature matching using the scale-invariant feature transform.
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Methods for faster feature matching using the scale-invariant feature transform./
Author:
Treen, Geoffrey.
Description:
76 p.
Notes:
Source: Masters Abstracts International, Volume: 48-06, page: 3728.
Contained By:
Masters Abstracts International48-06.
Subject:
Engineering, Robotics. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR63824
ISBN:
9780494638248
Methods for faster feature matching using the scale-invariant feature transform.
Treen, Geoffrey.
Methods for faster feature matching using the scale-invariant feature transform.
- 76 p.
Source: Masters Abstracts International, Volume: 48-06, page: 3728.
Thesis (M.A.Sc.)--Carleton University (Canada), 2010.
A set of modular algorithms for efficiently finding SIFT correspondences in images or image archives is presented. The basic algorithm, called SIFT-HHM, exploits properties of the SIFT descriptor vector to find shortcuts to the most likely matches in two feature sets. SIFT-HHM converges approximately 15 times faster than a linear search, and, respectively, four and five times faster than PCA-SIFT and SURF at near-equivalent precision-recall performance.
ISBN: 9780494638248Subjects--Topical Terms:
1018454
Engineering, Robotics.
Methods for faster feature matching using the scale-invariant feature transform.
LDR
:01851nam 2200277 4500
001
1401691
005
20111017084431.5
008
130515s2010 ||||||||||||||||| ||eng d
020
$a
9780494638248
035
$a
(UMI)AAIMR63824
035
$a
AAIMR63824
040
$a
UMI
$c
UMI
100
1
$a
Treen, Geoffrey.
$3
1680842
245
1 0
$a
Methods for faster feature matching using the scale-invariant feature transform.
300
$a
76 p.
500
$a
Source: Masters Abstracts International, Volume: 48-06, page: 3728.
502
$a
Thesis (M.A.Sc.)--Carleton University (Canada), 2010.
520
$a
A set of modular algorithms for efficiently finding SIFT correspondences in images or image archives is presented. The basic algorithm, called SIFT-HHM, exploits properties of the SIFT descriptor vector to find shortcuts to the most likely matches in two feature sets. SIFT-HHM converges approximately 15 times faster than a linear search, and, respectively, four and five times faster than PCA-SIFT and SURF at near-equivalent precision-recall performance.
520
$a
A PCA-based binning algorithm that can be combined with SIFT-HHM is presented to address the content-based image retrieval problem. Our experiments show this combined approach to be preferable over current tree-based methods for a number of reasons. Most significantly, it will converge approximately three times faster than the current state ofthe art. Secondly, database build times are less than 10% of those for constructing a k-means tree. Finally, we note simplicity of storage, scalability, and suitability to distributed processing as incidental benefits.
590
$a
School code: 0040.
650
4
$a
Engineering, Robotics.
$3
1018454
650
4
$a
Artificial Intelligence.
$3
769149
650
4
$a
Computer Science.
$3
626642
690
$a
0771
690
$a
0800
690
$a
0984
710
2
$a
Carleton University (Canada).
$3
1018407
773
0
$t
Masters Abstracts International
$g
48-06.
790
$a
0040
791
$a
M.A.Sc.
792
$a
2010
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR63824
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
W9164830
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