Title:
Tracking Through Clutter Using Graph Cuts
Tracking Through Clutter Using Graph Cuts
Author(s)
Malcolm, James G.
Rathi, Yogesh
Tannenbaum, Allen R.
Rathi, Yogesh
Tannenbaum, Allen R.
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Abstract
The standard graph cut technique is a robust method for globally optimal image segmentation. However, because of its global nature, it is prone to capture outlying areas similar to the object of interest. This paper proposes a novel method to constrain the standard graph cut technique for tracking objects in a region of interest. By introducing an additional penalty on pixels based upon their distance from a region of interest, segmentation is biased to remain in this area. We employ a filter which predicts the location of the
object. The distance penalty is then centered at this location and adaptively
scaled based on prediction confidence. This method tracks at real-time rates
and easily generalizes to tracking multiple noninteracting objects.
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Date Issued
2007-09
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Text
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Proceedings