The Coupled Depth/Slope Approach to Surface Reconstruction
Item
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Title
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en_US
The Coupled Depth/Slope Approach to Surface Reconstruction
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Creator
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en_US
Harris, John G.
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Date
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2004-10-20T20:02:52Z
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Date Available
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2004-10-20T20:02:52Z
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Date Issued
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en_US
1986-06-01
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Identifier
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en_US
AITR-908
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Abstract
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en_US
Reconstructing a surface from sparse sensory data is a well known problem in computer vision. Early vision modules typically supply sparse depth, orientation and discontinuity information. The surface reconstruction module incorporates these sparse and possibly conflicting measurements of a surface into a consistent, dense depth map. The coupled depth/slope model developed here provides a novel computational solution to the surface reconstruction problem. This method explicitly computes dense slope representation as well as dense depth representations. This marked change from previous surface reconstruction algorithms allows a natural integration of orientation constraints into the surface description, a feature not easily incorporated into earlier algorithms. In addition, the coupled depth/ slope model generalizes to allow for varying amounts of smoothness at different locations on the surface. This computational model helps conceptualize the problem and leads to two possible implementations- analog and digital. The model can be implemented as an electrical or biological analog network since the only computations required at each locally connected node are averages, additions and subtractions. A parallel digital algorithm can be derived by using finite difference approximations. The resulting system of coupled equations can be solved iteratively on a mesh-pf-processors computer, such as the Connection Machine. Furthermore, concurrent multi-grid methods are designed to speed the convergence of this digital algorithm.
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Extent
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en_US
80 p.
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7912060 bytes
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2975556 bytes
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Format
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application/postscript
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application/pdf
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Language
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en_US
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Relation
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en_US
AITR-908