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...
We describe how to model the appearance of a 3-D object using multiple views, learn such a model from training images, and use the model for object recognition. The model uses pro...
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 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 address the structure-from-motionproblem in the context of head modeling from video sequences for which calibration data is not available. This task is made challenging by the ...