The background primal sketch: an approach for tracking moving objects
Machine Vision and Applications
Face Recognition: Features Versus Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
A cascade face recognition system using hybrid feature extraction
Digital Signal Processing
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In this paper, we propose a method to evaluate the possible recognition degree of a face, called face recognizability, before face recognition. If we can measure the recognizability, we can increase the system efficiency by avoiding recognizing the faces with poor recognizabilities. Based on the features of the orientation distribution on the face regions, we found the facial components. Then we collected lines on the face with major orientations. Last, we used the triangle formed by two eyes and mouth, the degree of the face shape symmetry and intensity symmetry to define the measurement of face recognizability. Experimental results show that recognizability can be used as a measurement to determine whether we need to perform face recognition or not.