We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Several leading techniques: Principal Compo...
— This paper addresses recognition of human actions under view changes. We explore self-similarities of action sequences over time and observe the striking stability of such meas...
Imran N. Junejo, Emilie Dexter, Ivan Laptev, Patri...
Magnetic confinement fusion tokamaks are complex devices where a large amount of power is required to make the fusion reactions happen. In such experimental conditions, Plasma Faci...
We have developed a computer vision system, including both facial feature extraction and recognition, that automatically discriminates among subtly different facial expressions. E...
James Jenn-Jier Lien, Takeo Kanade, Jeffrey F. Coh...
We approach recognition in the framework of deformable shape matching, relying on a new algorithm for finding correspondences between feature points. This algorithm sets up corres...