Pose estimation, model refinement, and enhanced visualization usingvideo
Hsu, S.
Samarasekera, S.
Kumar, R.
Sawhney, H.S.
Sarnoff Corp., Princeton, NJ;
This paper appears in: Computer Vision and Pattern Recognition, 2000. Proceedings. IEEE Conference on
Publication Date: 2000
Volume: 1,
On page(s): 488-495 vol.1
Meeting Date: 06/13/2000 - 06/15/2000
Location: Hilton Head Island, SC, USA
ISBN: 0-7695-0662-3
References Cited: 19
INSPEC Accession Number: 6651674
Digital Object Identifier: 10.1109/CVPR.2000.855859
Current Version Published: 2002-08-06
Abstract
In this paper we present methods for exploitation and enhanced
visualization of video given a prior coarse untextured polyhedral model
of a scene. Since it is necessary to estimate the 3D poses of the moving
camera, we develop an algorithm where tracked features are used to
predict the pose between frames and the predicted poses are refined by a
coarse to fine process of aligning projected 3D model line segments to
oriented image gradient energy pyramids. The estimated poses can be used
to update the model with information derived from video, and to
re-project and visualize the video from different points of view with a
larger scene context. Via image registration, we update the placement of
objects in the model and the 3D shape of new or erroneously modeled
objects, then map video texture to the model. Experimental results are
presented for long aerial and ground level videos of a large-scale urban
scene
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