Paper Title
Face Hallucination and Recognition

Face recognition is effective when input probe is of high resolution. In public video surveillance captured face images are of low resolution. The general methods of face recognition consists steps; super resolving the LR input image followed by face recognition. Here, we present a framework based on SVD in which we perform face hallucination and recognition simultaneously. Accuracy of both hallucination and recognition is improved as we perform both of them simultaneously. We represent each face image by using SVD. For each LR input face image possible images with same singular values are selected from database. These images are in LR-HR pairs. For reconstructing the HR face images certain mapping models are learned from selected LR-HR pairs, which are used to interpolate the two matrices in the SVD representation. This will give more reliable & effective estimation of HR face images. Index Terms— Face hallucination ; LR Face recognition; Mapping model; S VD.