We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
In this paper we will present a set of experiments using large digitalized collections of books to show that logical structures can be extracted with good quality when working at ...
Background: During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have...
Abstract This paper presents an approach to designing and implementing extensible computational models for perceiving systems based on a knowledge-driven joint inference approach. ...
Camera calibration methods, whether implicit or explicit, are a critical part of most 3D vision systems. These methods involve estimation of a model for the camera that produced t...