Computer Vision
Face Recognition: Features Versus Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modal Matching for Correspondence and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Face Recognition Using Feature Combination
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Matching and recognition using deformable intensity surfaces
ISCV '95 Proceedings of the International Symposium on Computer Vision
Complex Feature Recognition: A Bayesian Approach for Learning to Recognize Objects
Complex Feature Recognition: A Bayesian Approach for Learning to Recognize Objects
Journal of Cognitive Neuroscience
2D and 3D face recognition: A survey
Pattern Recognition Letters
Interest point detection using imbalance oriented selection
Pattern Recognition
Recognizing faces under facial expression variations and partial occlusions
SIP'08 Proceedings of the 7th WSEAS International Conference on Signal Processing
Illumination Invariant Face Recognition under Various Facial Expressions and Occlusions
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
A Dynamic Programming Technique for Optimizing Dissimilarity-Based Classifiers
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Sensitivity analysis of partitioning-based face recognition algorithms on occlusions
AEE'07 Proceedings of the 6th conference on Applications of electrical engineering
A multiple combining method for optimizing dissimilarity-based classification
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
Local feature based 3d face recognition
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
| Hi-index | 0.00 |
The utility of face recognition for multimedia indexing is enhanced by using accurate detection and alignment of salient invariant face features. The face recognition can be performed using template matching or a feature-based-approach, but both these methods suffer from occlusion and require an a priori model for extracting information. To avoid these drawbacks, we present in this paper a complete scheme for face recognition based on salient feature extraction in challenging conditions, which is performed without an a priori or learned model. These features are used in a matching process that overcomes occlusion effects and facial expressions using the dynamic space warping which aligns each feature in the query image, if possible, with its corresponding feature in the gallery set. Thus, we make face recognition robust to low frequency variations (like the presence of occlusion, etc) as well as to high frequency variations (like expression, gender, etc). A maximum likelihood scheme is used to make the recognition process more precise, as is shown in the experiments.