Towards more efficient and flexible face image deblurring using robust salient face landmark detection

Recent years have witnessed great progress in image deblurring. However, as an important application case, the deblurring of face images has not been well studied. Most existing face deblurring methods rely on exemplar set construction and candidate matching, which not only cost much computation time but also are vulnerable to possible complex or exaggerated face variations. To address the aforementioned problems, we propose a novel face deblurring method by integrating classical L (0) deblurring approach with face landmark detection. A carefully tailored landmark detector is used to detect the main face contours. Then the detected contours are used as salient edges to guide the blind image deconvolution. Extensive experimental results demonstrate that the proposed method can better handle various complex face poses, shapes and expressions while greatly reducing computation time, as compared with existing state-of-the-art approaches.