東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Analysis of the effects of image reg...

Voynichka, Iliana.

Linked to FindBook

Google Book

Amazon

博客來

Analysis of the effects of image registration, template selection and partial information compilation on facial recognition accuracy.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Analysis of the effects of image registration, template selection and partial information compilation on facial recognition accuracy./
Author:	Voynichka, Iliana.
Description:	57 p.
Notes:	Source: Masters Abstracts International, Volume: 51-06.
Contained By:	Masters Abstracts International51-06(E).
Subject:	Engineering, Computer. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1522945
ISBN:	9781303149047

Analysis of the effects of image registration, template selection and partial information compilation on facial recognition accuracy.
Voynichka, Iliana.

Analysis of the effects of image registration, template selection and partial information compilation on facial recognition accuracy. - 57 p.

Source: Masters Abstracts International, Volume: 51-06.

Thesis (M.S.)--University of Massachusetts Lowell, 2013.

Fisherface-based, Eigenface-based and Direct Correlation-based facial recognition methods are often applied approaches for facial recognition. As it is known, these methods are highly affected by noise, illumination and other artifacts. Even though these methods have been around for more than twenty years, what additional factors affect their accuracy have not been accordingly studied as of yet. The main contribution of this thesis is the analysis and the investigation of how and what affects the recognition accuracy of Eigenface-based, Fisherface-based and Direct Correlation-based methods. In particular we present a facial recognition system that applies these three facial recognition algorithms to various databases containing images that have been preprocessed and/or grouped in different ways based on some proposed criteria. We show the effects on recognition accuracy of the usage of registered vs. raw images, the size and selection of the training templates, and the selection of the amount and type of information contained in the face images. Finally experimental results are presented to demonstrate the potential value and importance of each of these proposed factors on facial recognition.

ISBN: 9781303149047Subjects--Topical Terms:

1669061
Engineering, Computer.

Analysis of the effects of image registration, template selection and partial information compilation on facial recognition accuracy.
LDR:02126nam a2200277 4500 001 1959575
005 20140520124443.5
008 150210s2013 ||||||||||||||||| ||eng d
020 $a 9781303149047
035 $a (MiAaPQ)AAI1522945
035 $a AAI1522945
040 $a MiAaPQ $c MiAaPQ
100 1 $a Voynichka, Iliana. $3 2095034
245 1 0 $a Analysis of the effects of image registration, template selection and partial information compilation on facial recognition accuracy.
300 $a 57 p.
500 $a Source: Masters Abstracts International, Volume: 51-06.
500 $a Adviser: Dalila B. Megherbi.
502 $a Thesis (M.S.)--University of Massachusetts Lowell, 2013.
520 $a Fisherface-based, Eigenface-based and Direct Correlation-based facial recognition methods are often applied approaches for facial recognition. As it is known, these methods are highly affected by noise, illumination and other artifacts. Even though these methods have been around for more than twenty years, what additional factors affect their accuracy have not been accordingly studied as of yet. The main contribution of this thesis is the analysis and the investigation of how and what affects the recognition accuracy of Eigenface-based, Fisherface-based and Direct Correlation-based methods. In particular we present a facial recognition system that applies these three facial recognition algorithms to various databases containing images that have been preprocessed and/or grouped in different ways based on some proposed criteria. We show the effects on recognition accuracy of the usage of registered vs. raw images, the size and selection of the training templates, and the selection of the amount and type of information contained in the face images. Finally experimental results are presented to demonstrate the potential value and importance of each of these proposed factors on facial recognition.
590 $a School code: 0111.
650 4 $a Engineering, Computer. $3 1669061
650 4 $a Computer Science. $3 626642
690 $a 0464
690 $a 0984
710 2 $a University of Massachusetts Lowell. $3 1017839
773 0 $t Masters Abstracts International $g 51-06(E).
790 $a 0111
791 $a M.S.
792 $a 2013
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1522945