The spatial distribution of gray level intensities in an image can be naturally modeled using Markov random field (MRF) models. We develop and investigate the performance of face detection algorithms derived from MRF considerations. For enhanced detection, the MRF models are defined for every permutation of site indices (pixels) in the image. We find the optimal permutation that provides maximum discriminatory power to identify faces from nonfaces. The methodology presented here is a generalization of the face detection algorithm described previously where a most discriminating Markov chain model was used. The MRF models successfully detect faces in a number of test images.
Markov face models
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 ; 2 ; 680-687 vol.2
2001-01-01
1083158 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
British Library Conference Proceedings | 2001
|Using Hidden Markov Models and Wavelets for Face Recognition
British Library Conference Proceedings | 2003
|Video-Based Face Recognition Using Adaptive Hidden Markov Models
British Library Conference Proceedings | 2003
|