Sparse representation theory has been increasingly used in the fields of signal processing and machine learning. The standard sparse models are not invariant to spatial transform...
This paper addresses the supervised classification of remote-sensing images in problems characterized by relatively small-size training sets with respect to the input feature spac...
This paper suggests a high-level continuous image model for planar star-shaped objects. Under this model, a planar object is a stochastic deformation of a star-shaped template. The...
In online tracking, the tracker evolves to reflect variations in object appearance and surroundings. This updating process is formulated as a supervised learning problem, thus a ...
This paper addresses the problem of calibrating a pinhole camera from images of an isoceles trapezoid. Assuming a unit aspect ratio and zero skew, we introduce a novel and simple ...