Multiclient identification system using adaptive probabilistic model

Authors:
Chin-Teng Lin;Linda Siana;Yu-Wen Shou;Chien-Ting Yang
Affiliations:
Department of Electrical and Control Engineering, National Chiao Tung University, Hsinchu, Taiwan;Department of Electrical and Control Engineering, National Chiao Tung University, Hsinchu, Taiwan;Department of Computer and Communication Engineering, China University of Technology, Hsinchu, Taiwan;Department of Electrical and Control Engineering, National Chiao Tung University, Hsinchu, Taiwan
Venue:
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
Year:
2010

Citing 14
Cited 0

Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces

IEEE Transactions on Pattern Analysis and Machine Intelligence
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition by Elastic Bunch Graph Matching

IEEE Transactions on Pattern Analysis and Machine Intelligence
Active Appearance Models

IEEE Transactions on Pattern Analysis and Machine Intelligence
Biometrics, Personal Identification in Networked Society: Personal Identification in Networked Society

Biometrics, Personal Identification in Networked Society: Personal Identification in Networked Society
A decision-theoretic generalization of on-line learning and an application to boosting

EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
Face Recognition under Varying Views

BMVC '00 Proceedings of the First IEEE International Workshop on Biologically Motivated Computer Vision
Face Recognition Under Varying Pose

Face Recognition Under Varying Pose
A General Framework for Object Detection

ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Face recognition: A literature survey

ACM Computing Surveys (CSUR)
Robust Real-Time Face Detection

International Journal of Computer Vision
Eigenfaces for recognition

Journal of Cognitive Neuroscience
A survey of approaches and challenges in 3D and multi-modal 3D+2D face recognition

Computer Vision and Image Understanding
Face recognition: a convolutional neural-network approach

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper aims at integrating detection and identification of human faces in a more practical and real-time face recognition system. The proposed face detection system is based on the cascade Adaboost method to improve the precision and robustness toward unstable surrounding lightings. Our Adaboost method innovates to adjust the environmental lighting conditions by histogram lighting normalization and to accurately locate the face regions by a region-based-clustering process as well. We also address on the problem of multi-scale faces in this paper by using 12 different scales of searching windows and 5 different orientations for each client in pursuit of the multi-view independent face identification. There are majorly two methodological parts in our face identification system, including PCA (principal component analysis) facial feature extraction and adaptive probabilisticmodel (APM). The structure of our implemented APM with a weighted combination of simple probabilistic functions constructs the likelihood functions by the probabilistic constraint in the similarity measures. In addition, our proposed method can online add a new client and update the information of registered clients due to the constructed APM. The experimental results eventually show the superior performance of our proposed system for both offline and real-time online testing.