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 ...
A new method for tracking contours of moving objects in clutter is presented. For a given object, a model of its contours is learned from training data in the form of a subset of c...
We propose a Bayesian framework for representing and recognizing local image motion in terms of two basic models: translational motion and motion boundaries. Motion boundaries are ...
Linear parameterized models of optical flow, particularly affine models, have become widespread in image motion analysis. The linear model coefficients are straightforward to estim...
David J. Fleet, Michael J. Black, Yaser Yacoob, Al...
An overview is given of a novel vision system for locating, recognising and tracking multiple vehicles, using a single monocular camera mounted on a moving vehicle1 . 3D model-bas...
James M. Ferryman, Stephen J. Maybank, Anthony D. ...
In this paper we show that a classic optical ow technique by Nagel and Enkelmann (1986) can be regarded as an early anisotropic di usion method with a di usion tensor. We introduc...
In this paper we first overview the main concepts of Statistical Learning Theory, a framework in which learning from examples can be studied in a principled way. We then briefly di...
Optical flow provides a constraint on the motion of a deformable model. We derive and solve a dynamic system incorporating flow as a hard constraint, producing a model-based least...