We present a new class of statistical models for part-based object recognition. These models are explicitly parametrized according to the degree of spatial structure that they can ...
David J. Crandall, Pedro F. Felzenszwalb, Daniel P...
While low-dimensional image representations have been very popular in computer vision, they suffer from two limitations: (i) they require collecting a large and varied training se...
We present a method for live grouping of feature points into persistent 3D clusters as a single camera browses a static scene, with no additional assumptions, training or infrastr...
The problem of recognizing classes of objects as opposed to special instances requires methods of comparing images that capture the variation within the class while they discrimina...
This paper addresses the problem of recognizing objects in large image databases. The method is based on local characteristics which are invariant to simzlarity transformations in...