3D face recognition for partial data using Semi-Coupled Dictionary Learning
3D face recognition for partial data is a very challenging task. The task is even more challenging when the gallery sample originates from one side of the face while the probe sample originates from the other. We present a new method for computing the similarity of partial 3D data for the purpose of face recognition. This method improves upon an existing Semi-Coupled Dictionary Learning method by computing a jointly-optimized solution that incorporates the reconstruction cost, the discrimination cost and the semi-coupling cost. Our experiments demonstrate that this method can improve the recognition performance of existing state-of-the-art wavelet signatures used for 3D face recognition.