Now showing items 1-5 of 5
View-Based Models of 3D Object Recognition and Class-Specific Invariances
This paper describes the main features of a view-based model of object recognition. The model tries to capture general properties to be expected in a biological architecture for object recognition. The basic module is a ...
Associative Learning of Standard Regularizing Operators in Early Vision
(MIT Artificial Intelligence Laboratory, 1984-12)
Standard regularization methods can be used to solve satisfactorily several problems in early vision, including edge detection, surface reconstruction, the computation of motion and the recovery of color. In this paper, ...
Observations on Cortical Mechanisms for Object Recognition andsLearning
This paper sketches a hypothetical cortical architecture for visual 3D object recognition based on a recent computational model. The view-centered scheme relies on modules for learning from examples, such as Hyperbf-like ...
Learning a Color Algorithm from Examples
We show that a color algorithm capable of separating illumination from reflectance in a Mondrian world can be learned from a set of examples. The learned algorithm is equivalent to filtering the image data---in which ...
Visual Attention in Brains and Computers
Existing computer programs designed to perform visual recognition of objects suffer from a basic weakness: the inability to spotlight regions in the image that potentially correspond to objects of interest. The brain's ...