[Gzz-commits] manuscripts ./gzigzag.bib Paper/paper.tex

[Janne V. Kujala]

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 ------------------