Face authentication using the trace transform

We introduce a face representation, the shape trace transform (STT), for recognizing faces in an authentication system. The STT offers an alternative representation for faces that has a very high discriminatory power. We estimate the dissimilarity between two shapes by a new measure. We propose the Hausdorff context. Reinforcement learning is used to search the optimal parameters of the algorithm, for which the within class variance of the STT is minimized. This research demonstrates that the proposed method provides a new way for face representation. Our system is verified with experiments on the XM2VTS database.