Blinking-based live face detection using conditional random fields

Authors:
Lin Sun;Gang Pan;Zhaohui Wu;Shihong Lao
Affiliations:
Dept. of Computer Science, Zhejiang University, Hangzhou, P. R. China;Dept. of Computer Science, Zhejiang University, Hangzhou, P. R. China;Dept. of Computer Science, Zhejiang University, Hangzhou, P. R. China;Sensing and Control Technology Laboratory, OMRON Corporation, Japan
Venue:
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Year:
2007

Citing 11
Cited 0

A decision-theoretic generalization of on-line learning and an application to boosting

Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
The visual analysis of human movement: a survey

Computer Vision and Image Understanding
The FERET Evaluation Methodology for Face-Recognition Algorithms

IEEE Transactions on Pattern Analysis and Machine Intelligence
BioID: A Multimodal Biometric Identification System

Computer
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data

ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
The Representation and Recognition of Human Movement Using Temporal Templates

CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Shallow parsing with conditional random fields

NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Conditional Random Fields for Contextual Human Motion Recognition

ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Evaluating Liveness by Face Images and the Structure Tensor

AUTOID '05 Proceedings of the Fourth IEEE Workshop on Automatic Identification Advanced Technologies
Biometrics: Personal Identification in Networked Society

Biometrics: Personal Identification in Networked Society
Efficiently inducing features of conditional random fields

UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a blinking-based liveness detection method for human face using Conditional Random Fields (CRFs). Our method only needs a web camera for capturing video clips. Blinking clue is a passive action and does not need the user to to any hint, such as speaking, face moving. We model blinking activity by CRFs, which accommodates long-range contextual dependencies among the observation sequence. The experimental results demonstrate that the proposed method is promising, and outperforms the cascaded Adaboost method and HMM method.