Identification of human faces based on isodensity maps
Pattern Recognition
Feature extraction from faces using deformable templates
International Journal of Computer Vision
Automatic Interpretation and Coding of Face Images Using Flexible Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Support Vector Machines for 3D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Analytic-to-Holistic Approach for Face Recognition Based on a Single Frontal View
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrating Faces and Fingerprints for Personal Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robot Vision
Digital Image Processing
Face Recognition: Features Versus Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
System for the recognition of human faces
IBM Systems Journal
A robust method for detecting facial orientation in infrared images
Pattern Recognition
Ring-to-line mapping and orientation invariant transform for Chinese seal character recognition
International Journal of Computer Mathematics
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In this face recognition research, the head is fixed when a photograph is taken. The infrared diodes provide the only illumination. In front of the CCD camera, a light filter lens is used to filter all other light. After the photograph is taken, the eyebrows, eyes, nostrils, lips, and face contour are extracted separately. The shape, size, object-to-object distance, center and orientation are found for each extracted object. The techniques to solve the object shifting and rotating problems are investigated. Image subtraction is used to examine the geometric differences of the two different faces. The obtained classifying data in this research can accurately classify different people's faces.