By Topic

Video-based face authentication using appearance models and HMMs

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ke-Zhao Chen ; Dept. of Comput. Sci. & Inf. Eng., National Chung Cheng Univ., Chiayi, Taiwan ; Yao-Jen Chang ; Chia-Wen Lin

In this paper, we propose a novel face authentication scheme using the active appearance model (AAM) and the hidden Markov model (HMM). The proposed face authentication system can be divided into two parts. First, the AAM is used to extract the low-dimensional feature vectors including combined texture and shape information of individual face images. The extracted feature vectors are further classified into several clusters using vector quantization. The clustered feature vectors are then characterized using HMMs to make full use of the temporal information across the face images. After all parameters in the HMMs are calculated, we can dynamically determine the thresholds for face authentication. An iterative algorithm is also proposed to automatically determine a suitable number of HMM states and a suitable number of observation classes to achieve good authentication accuracy. The experimental results show the efficacy of the proposed method

Published in:

2006 IEEE International Symposium on Circuits and Systems

Date of Conference:

21-24 May 2006