Lab meeting 5 Jan, 2007(Atwood): Plan-view trajectory estimation with dense stereo background models

Title: Plan-view trajectory estimation with dense stereo background models
Auther: Darrell, T.; Demirdjian, D.; Checka, N.; Felzenszwalb, P.

from ICCV 2001.

Abstract:

In a known environment, objects may be tracked in multiple views using a set of background models. Stereo-based models can be illumination-invariant, but often have undefined values which inevitably lead to foreground classification errors. We derive dense stereo models for object tracking using long-term, extended dynamic-range imagery, and by detecting and interpolating uniform but unoccluded planar regions. Foreground points are detected quickly in new images using pruned disparity search. We adopt a “late-segmentation” strategy, using an integrated plan-view density representation. Foreground points are segmented into object regions only when a trajectory is finally estimated, using a dynamic programming-based method. Object entry and exit are optimally determined and are not restricted to special spatial zones


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