Title :
Video-based face authentication using appearance models and HMMs
Author :
Chen, Ke-Zhao ; Chang, Yao-Jen ; Lin, Chia-Wen
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., National Chung Cheng Univ., Chiayi
Abstract :
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
Keywords :
face recognition; feature extraction; hidden Markov models; image classification; image texture; message authentication; vector quantisation; video signal processing; HMM; active appearance model; feature classification; feature extraction; hidden Markov model; image texture; iterative algorithm; vector quantization; video-based face authentication; Active appearance model; Active shape model; Authentication; Biometrics; Data mining; Face detection; Face recognition; Feature extraction; Fingerprint recognition; Hidden Markov models;
Conference_Titel :
Circuits and Systems, 2006. ISCAS 2006. Proceedings. 2006 IEEE International Symposium on
Conference_Location :
Island of Kos
Print_ISBN :
0-7803-9389-9
DOI :
10.1109/ISCAS.2006.1692635