Head pose estimation using simple local gabor binary pattern

Authors:
Weijun Hu;Bingpeng Ma;Xiujuan Chai
Affiliations:
School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China;School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China;Key Lab of Intelligent Information Processing of Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China
Venue:
CCBR'11 Proceedings of the 6th Chinese conference on Biometric recognition
Year:
2011

Citing 9
Cited 0

Face Recognition by Elastic Bunch Graph Matching

IEEE Transactions on Pattern Analysis and Machine Intelligence
FotoFile: a consumer multimedia organization and retrieval system

Proceedings of the SIGCHI conference on Human Factors in Computing Systems
View-Based Active Appearance Models

FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Head Pose Estimation using Fisher Manifold Learning

AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Local Gabor Binary Pattern Histogram Sequence (LGBPHS): A Novel Non-Statistical Model for Face Representation and Recognition

ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Graph Embedded Analysis for Head Pose Estimation

FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
The application of extended geodesic distance in head poses estimation

ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Head Yaw Estimation From Asymmetry of Facial Appearance

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a novel method named simple Local Gabor Binary Pattern method (sLGBP) is presented to improve the accuracy of head pose estimation. The motivation of sLGBP comes from the great success of Local Gabor Binary Pattern (LGBP) in many areas. Considering the relationship between the symmetry of face image and the head pose, the Gabor filters and the LBP operators in sLGBP are all based on the one-dimension. By this way, feature extracted by sLGBP is more related to the head pose while the compute efficiency is improved greatly. To show the effectiveness of sLGBP, we compared them with other methods under two different databases. The results of the experiments show that the proposed methods can improve the accuracy of head pose estimation.