Dictionary learning is a challenging theme in computer vision. The basic goal is to learn a sparse representation from an overcomplete basis set. Most existing approaches employ a...
In this paper we present a generative, high resolution face representation which extends the well-known active appearance model (AAM)[5, 6, 7] with two additional layers. (i) One ...
An image representation framework based on structured sparse model selection is introduced in this work. The corresponding modeling dictionary is comprised of a family of learned ...
This paper presents a novel framework for recognition of facial action unit (AU) combinations by viewing the classification as a sparse representation problem. Based on this framew...
Mohammad H. Mahoor, Mu Zhou, Kevin L. Veon, Seyed ...
We propose a joint representation and classification framework that achieves the dual goal of finding the most discriminative sparse overcomplete encoding and optimal classifier p...