A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
Labelling sets of 2-D image features as model features is a constraint satisfaction problem that occurs in modelbased vision. The labelling must be consistent with constraints that describe how image features originating from the modelled object would appear in the image. This paper discusses how an assumption-based truth maintenance system, ATMS, can be used to solve such a constraint satisfaction problem. The ATMS is used to limit the number of constraints applied, and to represent thedoi:10.5244/c.2.2 dblp:conf/bmvc/BodingtonSB88 fatcat:d65srcw5ybbrbftsng6xbgxzba