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Dr. Richard Mann
Monday, October 15, 2007, 01:00pm - 02:00pm
University of Waterloo, School of Computer Science, Ontario, CANADA
Classical methods for measuring image motion by computer have concentrated on
the cases of optical flow in which the motion field is continuous, or layered
motion in which the motion field is made up a small number of depth planes.
Here we introduce a third natural category which we call optical snow.
Optical snow arises in many natural situations such as camera motion in a
highly cluttered 3-D scene, or a passive observer watching a snowfall.
Optical snow yields dense motion parallax with depth discontinuities occurring
near all image points. As such, constraints on smoothness or even smoothness
in layers do not apply.
We present a method for measuring optical snow based on a Fourier analyis of
motion. Next we show how local estimates of motion parallax are sufficient to
estimate camera motion (egomotion) directly, without first computing optical
flow. We demonstrate the effectiveness of the method for both synthetic and
real image sequences.
This is joint work with Michael Langer (McGill University).