The Coupled Depth/Slope Approach to Surface Reconstruction

Item

Title
en_US The Coupled Depth/Slope Approach to Surface Reconstruction
Creator
en_US Harris, John G.
Date
2004-10-20T20:02:52Z
Date Available
2004-10-20T20:02:52Z
Date Issued
en_US 1986-06-01
Identifier
en_US AITR-908
uri
http://hdl.handle.net/1721.1/6859
Abstract
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.
Extent
en_US 80 p.
7912060 bytes
2975556 bytes
Format
application/postscript
application/pdf
Language
en_US
Relation
en_US AITR-908
Item sets
AI Technical Reports (1964 - 2004)