Face Recognition with CLNF for Uncontrolled Occlusion Faces

Even though there has been enormous research in facial analysis and more sophisticated algorithm, face recognition fails drastically in real time when the facial images are occluded. This paper explains the algorithm and technical concepts behind the high accurate face recognition systems for a 2D frontal images with occlusion for a business requirments. Face recognition is implemented using Convolutional Neural Network (CNN) for training the occlusion images where the features are extracted by using Constrained Local Neural Field (CLNF). The work has done the real time uncontrolled occlusion dataset and recognized the face with the accuracy of 98.5% for the FAR of 0.