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Learning Dynamics of Complex Motions from Image Sequences
D. Reynard, A. Wildenberg, A. Blake and J. Marchant
4th European Conference on Computer Vision,
Cambridge, England, April 1996.
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Abstract
The performance of Active Contours in tracking is highly dependent on
the availability of an appropriate model of shape and motion, to use
as a predictor. Models can be hand-built, but it is far more effective
and less time-consuming to learn them from a training set. Techniques
to do this exist both for shape, and for shape and motion jointly.
This paper extends the range of shape and motion models in two
significant ways. The first is to model jointly the random variations
in shape arising within an object-class with those occuring during
object motion. The resulting algorithm is applied to tracking of
plants captured by a video camera mounted on an agricultural robot.
The second addresses the tracking of coupled objects such as head and
lips. In both cases, new algorithms are shown to make important
contributions to tracking performance.
