語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
A real-time method for facial detect...
~
Myers, Amanda.
FindBook
Google Book
Amazon
博客來
A real-time method for facial detection, tracking, and recognition.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
A real-time method for facial detection, tracking, and recognition./
作者:
Myers, Amanda.
面頁冊數:
66 p.
附註:
Source: Masters Abstracts International, Volume: 52-04.
Contained By:
Masters Abstracts International52-04(E).
標題:
Engineering, Computer. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1524692
ISBN:
9781303605062
A real-time method for facial detection, tracking, and recognition.
Myers, Amanda.
A real-time method for facial detection, tracking, and recognition.
- 66 p.
Source: Masters Abstracts International, Volume: 52-04.
Thesis (M.S.)--University of Massachusetts Lowell, 2013.
While there are many current approaches to solving the difficulties that come with detecting, tracking, and recognizing a given face in a video sequence, the difficulties arising when there are differences in pose, facial expression, orientation, lighting, scaling, and location remain an open research problem. In this thesis we perform the study and analysis of an approach for each of the three processes, namely a template face detection, tracking, and recognition. In the face detection approach we detect a given face by finding the pupils of the eyes within a given face. Then in the tracking approach, the face is tracked by searching within a region in the face for the eyes. Finally, in the recognition approach, the face is recognized by scaling and rotating the template image and comparing it to reference face images in a given database. The proposed algorithms are faster relatively to other existing iterative methods. Unlike such iterative methods, in our proposed method we do not estimate the face rotation angle or scaling factor by looking into all possible face rotations or scaling factors. In particular, in the proposed tracking/recognition method, we take a vector distance between the two eyes in a given face to estimate the face rotation and scaling factor relatively to the image coordinate system. This is done once and for each frame. The reference face images in the database are normalized with respect to face translation, rotation, and scaling. We show here how the proposed method to estimate a given face image template rotation and scaling factor leads to real-time template image rotation and scaling corrections. This allows the recognition algorithm to be less computationally complex than iterative methods.
ISBN: 9781303605062Subjects--Topical Terms:
1669061
Engineering, Computer.
A real-time method for facial detection, tracking, and recognition.
LDR
:02575nam a2200265 4500
001
1958848
005
20140512081837.5
008
150210s2013 ||||||||||||||||| ||eng d
020
$a
9781303605062
035
$a
(MiAaPQ)AAI1524692
035
$a
AAI1524692
040
$a
MiAaPQ
$c
MiAaPQ
100
1
$a
Myers, Amanda.
$3
2094072
245
1 2
$a
A real-time method for facial detection, tracking, and recognition.
300
$a
66 p.
500
$a
Source: Masters Abstracts International, Volume: 52-04.
500
$a
Adviser: Dalila Megherbi.
502
$a
Thesis (M.S.)--University of Massachusetts Lowell, 2013.
520
$a
While there are many current approaches to solving the difficulties that come with detecting, tracking, and recognizing a given face in a video sequence, the difficulties arising when there are differences in pose, facial expression, orientation, lighting, scaling, and location remain an open research problem. In this thesis we perform the study and analysis of an approach for each of the three processes, namely a template face detection, tracking, and recognition. In the face detection approach we detect a given face by finding the pupils of the eyes within a given face. Then in the tracking approach, the face is tracked by searching within a region in the face for the eyes. Finally, in the recognition approach, the face is recognized by scaling and rotating the template image and comparing it to reference face images in a given database. The proposed algorithms are faster relatively to other existing iterative methods. Unlike such iterative methods, in our proposed method we do not estimate the face rotation angle or scaling factor by looking into all possible face rotations or scaling factors. In particular, in the proposed tracking/recognition method, we take a vector distance between the two eyes in a given face to estimate the face rotation and scaling factor relatively to the image coordinate system. This is done once and for each frame. The reference face images in the database are normalized with respect to face translation, rotation, and scaling. We show here how the proposed method to estimate a given face image template rotation and scaling factor leads to real-time template image rotation and scaling corrections. This allows the recognition algorithm to be less computationally complex than iterative methods.
590
$a
School code: 0111.
650
4
$a
Engineering, Computer.
$3
1669061
690
$a
0464
710
2
$a
University of Massachusetts Lowell.
$3
1017839
773
0
$t
Masters Abstracts International
$g
52-04(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=1524692
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9253676
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入