BibTeX
@article{IJASEIT1,
author = {Kartika Firdausy and Balza Achmad},
title = {Automatic Frontal Face Pose Tracking for Face Recognition System},
journal = {International Journal on Advanced Science, Engineering and Information Technology},
volume = {1},
number = {4},
year = {2011},
pages = {399--402},
keywords = {face detection; face pose; pose tracking},
abstract = {Face recognition systems have been widely used in various security applications, for example in attendance system. The success of face recognition system relies on the trained face images as well as the face image captured that being recognized. Among the variables that determine the success of face recognition is face pose. Previous works showed that frontal face pose produced the best face recognition success rate. This paper proposes a face pose tracking subsystem that can be used as a filter so that only the frontal face pose that will be processed in the face recognition subsystem. The criteria for various face poses, i.e. frontal, tilted and turned, either left or right, have been formulated. Experimental results showed that the success rate of face recognition by implementing frontal face pose tracking can improve by 70.5%. However, it has trade off in reduced face image capture speed from 61 images per minute to 10 images per minute.},
issn = {2088-5334},
publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1},
doi = {10.18517/ijaseit.1.4.1}
}
EndNote
%A Firdausy, Kartika
%A Achmad, Balza
%D 2011
%T Automatic Frontal Face Pose Tracking for Face Recognition System
%B 2011
%9 face detection; face pose; pose tracking
%! Automatic Frontal Face Pose Tracking for Face Recognition System
%K face detection; face pose; pose tracking
%X Face recognition systems have been widely used in various security applications, for example in attendance system. The success of face recognition system relies on the trained face images as well as the face image captured that being recognized. Among the variables that determine the success of face recognition is face pose. Previous works showed that frontal face pose produced the best face recognition success rate. This paper proposes a face pose tracking subsystem that can be used as a filter so that only the frontal face pose that will be processed in the face recognition subsystem. The criteria for various face poses, i.e. frontal, tilted and turned, either left or right, have been formulated. Experimental results showed that the success rate of face recognition by implementing frontal face pose tracking can improve by 70.5%. However, it has trade off in reduced face image capture speed from 61 images per minute to 10 images per minute.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1
%R doi:10.18517/ijaseit.1.4.1
%J International Journal on Advanced Science, Engineering and Information Technology
%V 1
%N 4
%@ 2088-5334
IEEE
Kartika Firdausy and Balza Achmad,"Automatic Frontal Face Pose Tracking for Face Recognition System," International Journal on Advanced Science, Engineering and Information Technology, vol. 1, no. 4, pp. 399-402, 2011. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.1.4.1.
RefMan/ProCite (RIS)
TY - JOUR
AU - Firdausy, Kartika
AU - Achmad, Balza
PY - 2011
TI - Automatic Frontal Face Pose Tracking for Face Recognition System
JF - International Journal on Advanced Science, Engineering and Information Technology; Vol. 1 (2011) No. 4
Y2 - 2011
SP - 399
EP - 402
SN - 2088-5334
PB - INSIGHT - Indonesian Society for Knowledge and Human Development
KW - face detection; face pose; pose tracking
N2 - Face recognition systems have been widely used in various security applications, for example in attendance system. The success of face recognition system relies on the trained face images as well as the face image captured that being recognized. Among the variables that determine the success of face recognition is face pose. Previous works showed that frontal face pose produced the best face recognition success rate. This paper proposes a face pose tracking subsystem that can be used as a filter so that only the frontal face pose that will be processed in the face recognition subsystem. The criteria for various face poses, i.e. frontal, tilted and turned, either left or right, have been formulated. Experimental results showed that the success rate of face recognition by implementing frontal face pose tracking can improve by 70.5%. However, it has trade off in reduced face image capture speed from 61 images per minute to 10 images per minute.
UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1
DO - 10.18517/ijaseit.1.4.1
RefWorks
RT Journal Article
ID 1
A1 Firdausy, Kartika
A1 Achmad, Balza
T1 Automatic Frontal Face Pose Tracking for Face Recognition System
JF International Journal on Advanced Science, Engineering and Information Technology
VO 1
IS 4
YR 2011
SP 399
OP 402
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 face detection; face pose; pose tracking
AB Face recognition systems have been widely used in various security applications, for example in attendance system. The success of face recognition system relies on the trained face images as well as the face image captured that being recognized. Among the variables that determine the success of face recognition is face pose. Previous works showed that frontal face pose produced the best face recognition success rate. This paper proposes a face pose tracking subsystem that can be used as a filter so that only the frontal face pose that will be processed in the face recognition subsystem. The criteria for various face poses, i.e. frontal, tilted and turned, either left or right, have been formulated. Experimental results showed that the success rate of face recognition by implementing frontal face pose tracking can improve by 70.5%. However, it has trade off in reduced face image capture speed from 61 images per minute to 10 images per minute.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1
DO - 10.18517/ijaseit.1.4.1
