Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Binary Image Metrics
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Finding faces in cluttered scenes using random labeled graph matching
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Online face detection and user authentication
Proceedings of the 13th annual ACM international conference on Multimedia
Local Binary Patterns as an Image Preprocessing for Face Authentication
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Real time 2-D face detection using color ratios and K-mean clustering
Proceedings of the 44th annual Southeast regional conference
Facial feature extraction for face characterization
Proceedings of the 44th annual Southeast regional conference
Combined face recognition using wavelet packets and radial basis function neural network
CompSysTech '07 Proceedings of the 2007 international conference on Computer systems and technologies
Analytic Phase-based Representation for Face Recognition
ICAPR '09 Proceedings of the 2009 Seventh International Conference on Advances in Pattern Recognition
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In today's world, the scope and applications of face recognition systems either as standalone or as an integrated module into a larger system cannot be belittled. Remarkable face recognition algorithms have been proposed in last decade offering towering levels of accuracy and precision. However, the flexibility and robustness of the existing systems remain highly questionable. To further intricate these problems, most of the face recognitions systems are designed under strict background constraints, conveniently ignoring variations in illumination and at the apex of the predicament, lies the intricacy involved in the creation and maintenance of training sets in the databases. Even the most sophisticated systems designed posed grave difficulties in deployment and required maintenance by skilled personnel, leading to poor response from the global market. With an objective to realize an intelligent, maintenance-free system with impeccable design, our research team developed an immaculate real-time face recognition system with dynamic training and enhanced multi-algorithm face recognition. The system would facilitate user-friendly, dynamic creation of training sets by means of an innovative approach which would make the need of skilled maintenance personnel obsolete. The proposed system has been comprehensively tested to achieve remarkable precision and accuracy of 99.9%. Proposed system archetype design would result in manifold applications in developing simplified face recognition systems (for enrolling masses) for institutions, business organizations, research labs, military applications, etc. for authentication and authorization purposes.