We propose the use of latent space models applied to local invariant features for object classification. We investigate whether using latent space models enables to learn patterns...
Florent Monay, Pedro Quelhas, Daniel Gatica-Perez,...
This paper presents an efficient and homogeneous paradigm for automatic acquisition and recognition of nonparametric shapes. Acquisition time varies from linear to cubic in the nu...
Abstract. Humans have the remarkable ability to generalize from binocular to monocular figure-ground segmentation of complex scenes. This is clearly evident anytime we look at a p...
Brian Mingus, Trent Kriete, Seth A. Herd, Dean Wya...
Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and object recognition. However, such descriptors are typically of ...
We develop a novel method for class-based feature matching across large changes in viewing conditions. The method (called MBE) is based on the property that when objects share a si...