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ICCV
2001
IEEE

Plan-View Trajectory Estimation with Dense Stereo Background Models

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Plan-View Trajectory Estimation with Dense Stereo Background Models
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 "latesegmentation" 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.
Trevor Darrell, David Demirdjian, Neal Checka, Ped
Added 15 Oct 2009
Updated 31 Oct 2009
Type Conference
Year 2001
Where ICCV
Authors Trevor Darrell, David Demirdjian, Neal Checka, Pedro F. Felzenszwalb
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