We address mid-level vision for the recognition of non-rigid objects. We align model and image using frame curves - which are object or "figure/ground" skeletons. Frame curves are computed, without discontinuities, using Curved Inertia Frames, a provably global scheme implemented on the Connection Machine, based on: non-cartisean networks; a definition of curved axis of inertia; and a ridge detector. I present evidence against frame alignment in human perception. This suggests: frame curves have a role in figure/ground segregation and in fuzzy boundaries; their outside/near/top/ incoming regions are more salient; and that perception begins by setting a reference frame (prior to early vision), and proceeds by processing convex structures.
Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/6792 |
Date | 01 April 1995 |
Creators | Subirana-Vilanova, J. Brian |
Source Sets | M.I.T. Theses and Dissertation |
Language | en_US |
Detected Language | English |
Format | 239 p., 48192029 bytes, 2356367 bytes, application/postscript, application/pdf |
Relation | AITR-1442 |
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