This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize ...
Abstract. In spite of over two decades of intense research, illumination and pose invariance remain prohibitively challenging aspects of face recognition for most practical applica...
The space of images is known to be a non-linear subspace that is difficult to model. This paper derives an algorithm that walks within this space. We seek a manifold through the ...
In this paper, we propose a probabilistic videobased facial expression recognition method on manifolds. The concept of the manifold of facial expression is based on the observatio...