We propose a new transductive learning algorithm for learning optimal linear representations that utilizes unlabeled data. We pose the problem of learning linear representations a...
— Optimal component analysis (OCA) uses a stochastic gradient optimization process to find optimal representations for general criteria and shows good performance in object reco...
We propose a method for interpolation between eigenspaces. Techniques that represent observed patterns as multivariate normal distribution have actively been developed to make it r...
Abstract. This paper presents a method to decompose a field of surface normals (needle-map). A diffusion process is used to model the flow of height information induced by a fi...
In this paper, we propose a novel approach for facial expression analysis and recognition. The proposed approach relies on tracked facial actions provided by an appearance-based 3...