SURFACE ORIENTATION FROM TEXTURE - IDEAL OBSERVERS, GENERIC OBSERVERSAND THE INFORMATION-CONTENT OF TEXTURE CUES

Authors
Citation
Dc. Knill, SURFACE ORIENTATION FROM TEXTURE - IDEAL OBSERVERS, GENERIC OBSERVERSAND THE INFORMATION-CONTENT OF TEXTURE CUES, Vision research (Oxford), 38(11), 1998, pp. 1655-1682
Citations number
34
Categorie Soggetti
Neurosciences,Ophthalmology
Journal title
ISSN journal
00426989
Volume
38
Issue
11
Year of publication
1998
Pages
1655 - 1682
Database
ISI
SICI code
0042-6989(1998)38:11<1655:SOFT-I>2.0.ZU;2-Y
Abstract
Perspective views of textured, planar surfaces provide a number of cue s about the orientations of the surfaces. These include the informatio n created by perspective scaling of texture elements (scaling), the in formation created by perspective foreshortening of texels (foreshorten ing) and, for textures composed of discrete elements, the information created by the effects of both scaling and foreshortening on the relat ive positions of texels (position). We derive a general form for ideal observers for each of these cues as they appear in images of spatiall y extended textures, (e.g. those composed of solid 2-D figures). As an application of the formulation, we derive a set of 'generic' observer s which we show perform near optimally for images of a broad range of surface textures, without special prior knowledge about the statistics of the textures. Using simulations of ideal observers, we analyze the informational structure of texture cues, including a quantification o f lower bounds on reliability for the three different cues, how cue re liability varies with slant angle and how it varies with field of view . We also quantify how strongly the reliability of the foreshortening cue depends on a prior assumption of isotropy. Finally, we extend the analysis to a naturalistic class of textures, showing that the informa tion content of textures particularly suited to psychophysical investi gation can be quantified, at least to a first-order approximation. The results provide an important computational foundation for psychophysi cal work on perceiving surface orientation from texture. (C) 1998 Else vier Science Ltd. All rights reserved.