This paper presents a general, trainable system for object detection in unconstrained, cluttered scenes. The system derives much of its power from a representation that describes a...
We present a method for assessing the likelihoodof a trajectory of an object through a scene consisting of a number of other objects. The closest points on the trajectory to the o...
Classical visual servoing techniques need a strong a priori knowledge of the shape and the dimensions of the observed objects. In this paper, we present how the 2 1/2 D visual serv...
The aim of this paper is to explore a linear geometric algorithm for recovering the three dimensional motion of a moving camera from image velocities. Generic similarities and diff...
We present an algorithm to estimate the parameters of a linear model in the presence of heteroscedastic noise, i.e., each data point having a different covariance matrix. The algor...
This paper describes a simple method of fast background subtraction based upon disparity verification that is invariant to arbitrarily rapid run-time changes in illumination. Using...
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...
We propose a method for detecting geometric structures in an image, without any a priori information. Roughly speaking, we say that an observed geometric event is "meaningful&...