Separation of Transparent Motion into Layers using Velocity-Tuned Mechanisms
Published in:
European Conf on Computer Vision
Springer, 1994.
Also available as:
MIT Media Laboratory Vision and Modeling
Technical Report 244.
This paper presents a model for the perception of transparently combined
moving images. We advocate a framework consisting of a local motion mechanism
which can operate in the presence of transparency, and a global mechanism
that integrates information across space. We present a new method for the
local motion testing mechanism, using ``donut'' velocity selective mechanisms
formed from the weighted combination of spatio-temporal energy units. This
method has the advantage over traditional methods that it does not fail
when there are multiple motions in the sequence. The global layer selection
mechanism attempts to account for the local velocity distributions with
a small set of global functions. Using donut mechanisms permits a simplified
layer selection optimization, in which inhibition between layers is determined
by the product of their predicted velocity distributions. With this scheme,
we demonstrate the decomposition of image sequences containing additively
combined multiple moving objects into a set of layers corresponding to each
object.
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