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[Gzz-commits] manuscripts ./gzigzag.bib Paper/paper.tex
From: |
Janne V. Kujala |
Subject: |
[Gzz-commits] manuscripts ./gzigzag.bib Paper/paper.tex |
Date: |
Mon, 24 Mar 2003 12:24:18 -0500 |
CVSROOT: /cvsroot/gzz
Module name: manuscripts
Changes by: Janne V. Kujala <address@hidden> 03/03/24 12:24:17
Modified files:
. : gzigzag.bib
Paper : paper.tex
Log message:
reorg
CVSWeb URLs:
http://savannah.gnu.org/cgi-bin/viewcvs/gzz/manuscripts/gzigzag.bib.diff?tr1=1.65&tr2=1.66&r1=text&r2=text
http://savannah.gnu.org/cgi-bin/viewcvs/gzz/manuscripts/Paper/paper.tex.diff?tr1=1.53&tr2=1.54&r1=text&r2=text
Patches:
Index: manuscripts/Paper/paper.tex
diff -u manuscripts/Paper/paper.tex:1.53 manuscripts/Paper/paper.tex:1.54
--- manuscripts/Paper/paper.tex:1.53 Mon Mar 24 11:24:27 2003
+++ manuscripts/Paper/paper.tex Mon Mar 24 12:24:17 2003
@@ -33,8 +33,8 @@
\begin{document}
\maketitle
-\font\foofonti = cmfrak scaled 2000
-\font\foofontii = qhvb scaled 2000
+%\font\foofonti = cmfrak scaled 2000
+%\font\foofontii = qhvb scaled 2000
\begin{abstract}
@@ -264,6 +264,7 @@
perceptually, for visualizing surface
orientation\cite{schweitzer83texturing,interrante97illustrating} and scalar or
vector fields\cite{ware95texture},
and statistically, as samples from a probability distribution on a random field
\cite{cross83markov,geman84stochastic}.
+% XXX: there's overlap between the enumerated cases
%Textures have also been modeled statistically,
%as samples from a probability distribution on a random field.
@@ -273,54 +274,7 @@
%depends only on the values of its neighborhood (local characteristics).
%XXX: resolution-dependency?
-% In this article, we apply texture shading to synthesize a large number
-% of unique textures for distinguishing virtual objects.
-
-\subsection{Texture perception}
-
-Psychophysical studies on texture perception have mostly concentrated
-on pre-attentive
-\emph{visual texture discrimination}\cite{julesz62visualpattern},
-the ability of human observers to effortlessly discriminate
-pairs of certain textures (see Bergen\cite{bergen91theories} for a review).
-%The term is often used interchangably with \emph{texture segregation},
-%the more specific task of finding the border between differently textured
-%areas (different phases of local characteristics at the
-%border can segregate otherwise indiscriminable textures).
-%
-%First experiments on computer-generated, unnatural textures in the 60s
-%\cite{julesz62visualpattern} led to proposals of discrimination models
-%based on the $N$th-order statistics of textures
-%(the joint distributions of the values at the corners of a randomly
-%placed (translated) $N$-gon for all different $N$-gons).
-%%and connectivity structures of certain micropatterns.
-%
-First discrimination models were based
-on the $N$th-order statistics of textures
-(the joint distributions of the values at the corners of a randomly
-placed (translated) $N$-gon for all different $N$-gons).
-However, the order of similarity in the statistics did not
-consistently explain discrimination performance, and certain
-pre-attentive local features were conjectured.
-
-Julesz\cite{julesz81textons} proposed that texture discrimination could be
-explained by the densities of textons, fundamental texture elements, such as
-elongated blobs, line terminators, and line crossings.
-However, the textons are hard to define formally.
-
-Much simpler filtering-based models can explain texture discrimination
-just as well \cite{bergen88earlyvision}.
-In these models, a bank of linear filters is applied to the texture followed
-by a nonlinearity and then another set of filters to extract features
-(see, e.g., \cite{heeger95pyramid} for an application).
-%In \cite{heeger95pyramid}, new textures with appearance similar
-%to a given texture are created by matching certain histograms
-%of filter responses.
-
-XXX: higher-level pre-attentive processes?
-
-%XXX: texture perception reviews
-
+%% XXX: this is not really texturing:
There have been studies on
mapping texture appearance to an Euclidian texture space
(see \cite{gurnsey01texturespace} and the references therein):
@@ -334,7 +288,70 @@
sufficient \cite{rao96texturenaming}, but often semantic connections cause the
similarity to be context-dependant, making it hard to assess the
dimensionality.
-% XXX: this is something we should experiment with our textures
+%% XXX: this is something we should experiment with our textures
+
+% In this article, we apply texture shading to synthesize a large number
+% of unique textures for distinguishing virtual objects.
+
+%\subsection{Texture perception}
+%
+%Psychophysical studies on texture perception have mostly concentrated
+%on pre-attentive
+%\emph{visual texture discrimination}\cite{julesz62visualpattern},
+%the ability of human observers to effortlessly discriminate
+%pairs of certain textures (see Bergen\cite{bergen91theories} for a review).
+%%The term is often used interchangably with \emph{texture segregation},
+%%the more specific task of finding the border between differently textured
+%%areas (different phases of local characteristics at the
+%%border can segregate otherwise indiscriminable textures).
+%%
+%%First experiments on computer-generated, unnatural textures in the 60s
+%%\cite{julesz62visualpattern} led to proposals of discrimination models
+%%based on the $N$th-order statistics of textures
+%%(the joint distributions of the values at the corners of a randomly
+%%placed (translated) $N$-gon for all different $N$-gons).
+%%%and connectivity structures of certain micropatterns.
+%%
+%First discrimination models were based
+%on the $N$th-order statistics of textures
+%(the joint distributions of the values at the corners of a randomly
+%placed (translated) $N$-gon for all different $N$-gons).
+%However, the order of similarity in the statistics did not
+%consistently explain discrimination performance, and certain
+%pre-attentive local features were conjectured.
+%
+%Julesz\cite{julesz81textons} proposed that texture discrimination could be
+%explained by the densities of textons, fundamental texture elements, such as
+%elongated blobs, line terminators, and line crossings.
+%However, the textons are hard to define formally.
+%
+%Much simpler filtering-based models can explain texture discrimination
+%just as well \cite{bergen88earlyvision}.
+%In these models, a bank of linear filters is applied to the texture followed
+%by a nonlinearity and then another set of filters to extract features
+%(see, e.g., \cite{heeger95pyramid} for an application).
+%%In \cite{heeger95pyramid}, new textures with appearance similar
+%%to a given texture are created by matching certain histograms
+%%of filter responses.
+%
+%XXX: higher-level pre-attentive processes?
+%
+%%XXX: texture perception reviews
+%
+%There have been studies on
+%mapping texture appearance to an Euclidian texture space
+%(see \cite{gurnsey01texturespace} and the references therein):
+%in the reported experiments, three dimensions have been sufficient
+%to explain most of the variation in the similarity judgements for
+%artificial textures.
+%However, the texture stimuli have been somewhat simple
+%(no color, lack of frequency-band interaction, etc.).
+%For some natural texture sets,
+%three dimensions have also been
+%sufficient \cite{rao96texturenaming}, but often semantic connections cause the
+%similarity to be context-dependant, making it hard to assess the
+%dimensionality.
+%% XXX: this is something we should experiment with our textures
\subsection{Focus+Context views}
@@ -525,26 +542,48 @@
we have to take into account the properties of the human
visual system.
-% The seed for randomly choosing
-% an easily distinguishable unique background from a
-% distribution based on
+Psychophysical studies on texture perception have mostly concentrated
+on pre-attentive
+\emph{visual texture discrimination}\cite{julesz62visualpattern},
+the ability of human observers to effortlessly discriminate
+pairs of certain textures (see Bergen\cite{bergen91theories} for a review).
+Nevertheless,
+discrimination models can provide insight on the pre-attentive
+processes underlying global perception.
-%providing an infinite source of unique backgrounds.
-%generating textures based on seed numbers [identity]
-The first stages
-of visual perception
-are fairly well known
-(see, e.g.,~Bruce et al\cite{bruce96visualperception}):
+Julesz\cite{julesz81textons} proposed that texture discrimination could be
+explained by the densities of textons, fundamental texture elements, such as
+elongated blobs, line terminators, and line crossings.
+However, the textons are hard to define formally.
+
+Much simpler filtering-based models can explain texture discrimination
+just as well \cite{bergen88earlyvision}.
+In these models, a bank of linear filters is applied to the texture followed
+by a nonlinearity and then another set of filters to extract features
+(see, e.g., Heeger\cite{heeger95pyramid}).
+There is also physiological evidence of filtering processes:
+%The first stages
+%of visual perception
+%are fairly well known
in the visual cortex, there are cells sensitive to different
-frequencies, orientations, and locations in the visual field.
+frequencies, orientations, and locations in the visual field
+(see, e.g.,~Bruce et al\cite{bruce96visualperception}).
+
On a higher level, the correlations between local features are combined
by forming contours and possibly
-other higher-level constructions.
+other higher-level constructions (see, e.g., \cite{saarinen97integration}).
These higher levels are not yet thoroughly understood;
some theories
(see, e.g., Biederman\cite{biederman87})
assume certain primitive shapes whose
structure facilitates recognition.
+
+% The seed for randomly choosing
+% an easily distinguishable unique background from a
+% distribution based on
+
+%providing an infinite source of unique backgrounds.
+%generating textures based on seed numbers [identity]
\begin{figure}
\centering
Index: manuscripts/gzigzag.bib
diff -u manuscripts/gzigzag.bib:1.65 manuscripts/gzigzag.bib:1.66
--- manuscripts/gzigzag.bib:1.65 Sun Mar 23 05:53:11 2003
+++ manuscripts/gzigzag.bib Mon Mar 24 12:24:17 2003
@@ -2652,6 +2652,17 @@
year = "1991",
}
address@hidden saarinen97integration,
+ author = "Saarinen, Jukka and Levi, Dennis M. and Shen, Bridgitte",
+ title = "Integration of local pattern elements into a global shape in human
vision",
+ journal = "Proceedings of the National Academy of Sciences U.S.A.",
+ volume = "94",
+ pages = "8267-8271",
+ month = "Jul",
+ year = "1997",
+ url = "http://www.pnas.org/cgi/reprint/94/15/8267.pdf",
+}
+
@comment ------------------
@comment MRF texture models
@comment ------------------
- [Gzz-commits] manuscripts ./gzigzag.bib Paper/paper.tex, Janne V. Kujala, 2003/03/06
- [Gzz-commits] manuscripts ./gzigzag.bib Paper/paper.tex, Janne V. Kujala, 2003/03/06
- [Gzz-commits] manuscripts ./gzigzag.bib Paper/paper.tex, Janne V. Kujala, 2003/03/08
- [Gzz-commits] manuscripts ./gzigzag.bib Paper/paper.tex, Janne V. Kujala, 2003/03/11
- [Gzz-commits] manuscripts ./gzigzag.bib Paper/paper.tex, Janne V. Kujala, 2003/03/12
- [Gzz-commits] manuscripts ./gzigzag.bib Paper/paper.tex, Janne V. Kujala, 2003/03/13
- [Gzz-commits] manuscripts ./gzigzag.bib Paper/paper.tex, Janne V. Kujala, 2003/03/14
- [Gzz-commits] manuscripts ./gzigzag.bib Paper/paper.tex, Janne V. Kujala, 2003/03/23
- [Gzz-commits] manuscripts ./gzigzag.bib Paper/paper.tex,
Janne V. Kujala <=
- [Gzz-commits] manuscripts ./gzigzag.bib Paper/paper.tex, Janne V. Kujala, 2003/03/29
- [Gzz-commits] manuscripts ./gzigzag.bib Paper/paper.tex, Janne V. Kujala, 2003/03/31
- [Gzz-commits] manuscripts ./gzigzag.bib Paper/paper.tex, Janne V. Kujala, 2003/03/31