annotate org/adelson-notes.org @ 66:eae81fa3a8e0

add camera timing idea.
author Robert McIntyre <rlm@mit.edu>
date Thu, 03 Oct 2013 17:42:48 -0400
parents
children 036fe1b13120
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rlm@66 1 #+title: Notes for "Special Topics in Computer Vision"
rlm@66 2 #+author: Robert McIntyre
rlm@66 3 #+email: rlm@mit.edu
rlm@66 4 #+description:
rlm@66 5 #+keywords:
rlm@66 6 #+SETUPFILE: ../../aurellem/org/setup.org
rlm@66 7 #+INCLUDE: ../../aurellem/org/level-0.org
rlm@66 8 #+babel: :mkdirp yes :noweb yes :exports both
rlm@66 9
rlm@66 10 * Fri Sep 27 2013
rlm@66 11
rlm@66 12 Lambertian surfaces are a special type of Matt surface. They reflect
rlm@66 13 light in all directions equally. They have only one parameter, the
rlm@66 14 amount of energy that is absorbed/re-emitted.
rlm@66 15
rlm@66 16 [[../images/adelson-checkerboard.jpg]]
rlm@66 17 #+caption: Lol checkerboard illusion.
rlm@66 18
rlm@66 19 Look into Helmholtz' stuff, it might be interesting. It was the
rlm@66 20 foundation of both vision and audition research. Seems to have took
rlm@66 21 a sort of Baysean approach to inferring how vision/audition works.
rlm@66 22
rlm@66 23 - Homomorphic filtering :: Oppenhiem, Schafer, Stockham, 1968. also
rlm@66 24 look at Stockham, 1972.
rlm@66 25
rlm@66 26 Edwin Land was Adelson's hero back in the day. He needed to create a
rlm@66 27 color photo for the Polaroid camera. In order to process for
rlm@66 28 automatic development of film, he had to get a good approximation for
rlm@66 29 the illumination/reflectance decomposition that humans do, which he
rlm@66 30 called Retinex.
rlm@66 31
rlm@66 32 Cornsweet square wave grating is cool.
rlm@66 33
rlm@66 34 - Retinex :: use derivatives to find illumination. Sort of
rlm@66 35 implicitly deals with edges, etc. Can't deal with
rlm@66 36 non-lambertian objects.
rlm@66 37
rlm@66 38
rlm@66 39 Adelson introduces the problem as an "inverse" problem, where you
rlm@66 40 try to "undo" the 3-d projection of the world on your retina.
rlm@66 41
rlm@66 42 On the functional view of vision : "What it takes" is to build a
rlm@66 43 model of the world in your head. The bare minimum to get success in
rlm@66 44 life is to have a model of the world. Even at the level of a single
rlm@66 45 cell, I think you still benefit from models.
rlm@66 46
rlm@66 47 Spatial propagation is ABSOLUTELY required to separate embossed
rlm@66 48 stuff from "painted" stuff. Edges, likewise, MUST have spatial
rlm@66 49 context to disambiguate. The filters we use to deal with edges must
rlm@66 50 have larger spatial context to work, and the spatial extent of this
rlm@66 51 context must be the ENTIRE visual field in some cases!
rlm@66 52
rlm@66 53 ------------------------------------------------------------
rlm@66 54
rlm@66 55 ** Illumination, shape, reflectance all at once
rlm@66 56
rlm@66 57 What if we tried to infer everything together? Some images are so
rlm@66 58 ambiguous it requires propagation from all three qualities to
rlm@66 59 resolve the ambiguity.
rlm@66 60
rlm@66 61 Brain has a competing painter, sculptor, and gaffer which each try
rlm@66 62 to "build" the things in the world. There is a cost to everything
rlm@66 63 such as paints, lights, and material, and then you try to optmize
rlm@66 64 some cost function using these primitives.
rlm@66 65
rlm@66 66
rlm@66 67 Horn, technical report, 1970