This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
17th International Conference on Pattern Recognition (ICPR'04) - Volume 1
Face Pose Estimation and its Application in Video Shot Selection
Cambridge UK
August 23-August 26
ISBN: 0-7695-2128-2
ASCII Text
x 
 
Zhiguang Yang, Haizhou Ai, Bo Wu, Shihong Lao, Lianhong Cai, "Face Pose Estimation and its Application in Video Shot Selection," Pattern Recognition, International Conference on, vol. 1, pp. 322-325, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 1, 2004.
 
 
BibTex
x
 
@article{ 10.1109/ICPR.2004.1334117,
author = {Zhiguang Yang and Haizhou Ai and Bo Wu and Shihong Lao and Lianhong Cai},
title = {Face Pose Estimation and its Application in Video Shot Selection},
journal ={Pattern Recognition, International Conference on},
volume = {1},
year = {2004},
issn = {1051-4651},
pages = {322-325},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.1334117},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Pattern Recognition, International Conference on
TI - Face Pose Estimation and its Application in Video Shot Selection
SN - 1051-4651
SP322
EP325
A1 - Zhiguang Yang,
A1 - Haizhou Ai,
A1 - Bo Wu,
A1 - Shihong Lao,
A1 - Lianhong Cai,
PY - 2004
KW - null
VL - 1
JA - Pattern Recognition, International Conference on
ER -
 
Zhiguang Yang, Tsinghua University, Beijing, China
Haizhou Ai, Tsinghua University, Beijing, China
Bo Wu, Tsinghua University, Beijing, China
Shihong Lao, Sensing Technology Laboratory, Omron Corporation
Lianhong Cai, Tsinghua University, Beijing, China
In this paper, a face pose estimation method and its application in video shot selection for face image preprocessing is introduced. The pose estimator is learned by a boosting regression algorithm called SquareLev.R [Boosting Methods for Regression] that learns poses from simple Haar-type features. It consists of two tree structured subsystems for the left-right angle and up-down angle respectively. As a specific application in video based face recognition, the best shot selection problem is discussed, which results in a real-time system that can automatically select the most frontal face from a video sequence.
Citation:
Zhiguang Yang, Haizhou Ai, Bo Wu, Shihong Lao, Lianhong Cai, "Face Pose Estimation and its Application in Video Shot Selection," icpr, vol. 1, pp.322-325, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 1, 2004
Usage of this product signifies your acceptance of the Terms of Use.