Face hallucination produces high-resolution facial images from low-resolution inputs. In this paper, we propose a facial-parts-based face hallucination method. Since our goal is face recognition rather than face reconstruction, the contour information of facial-parts (such as eyes) is important. This method reconstructs facial parts as entities instead of dividing them into small blocks. We obtain the contours of facial parts by using the Active Appearance Model (AAM), and transform training images based on contours. We confirm that the proposed method significantly enhances face recognition performance.
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