[Gzz-commits] manuscripts/Paper paper.tex

[Tuomas J. Lukka]

CVSROOT:        /cvsroot/gzz
Module name:    manuscripts
Changes by:     Tuomas J. Lukka <address@hidden>        03/03/06 05:50:21

Modified files:
        Paper          : paper.tex 

Log message:
        Assign the sections for now -- jvk, these are 'locks' on the sections, 
I'll be going to town and working on the marked sections.

CVSWeb URLs:
http://savannah.gnu.org/cgi-bin/viewcvs/gzz/manuscripts/Paper/paper.tex.diff?tr1=1.5&tr2=1.6&r1=text&r2=text

Patches:
Index: manuscripts/Paper/paper.tex
diff -u manuscripts/Paper/paper.tex:1.5 manuscripts/Paper/paper.tex:1.6
--- manuscripts/Paper/paper.tex:1.5     Thu Mar  6 02:44:01 2003
+++ manuscripts/Paper/paper.tex Thu Mar  6 05:50:20 2003
@@ -9,12 +9,12 @@
 
\newcommand{\url}[1]{{\fontsize{9pt}{8pt}\fontfamily{phv}\fontseries{c}\selectfont{#1}}}
 \newcommand{\hyp}{\discretionary{}{}{}}
 
-\def\censor#1{{\sffamily\tiny ${}^{\left<\hbox{censored}\,\right>}$}}
 
-\title{Representing Identity 
-%in Focus+Context Views 
-%Hardware-Accelerated 
-by Unique Background Textures}
+\title{Rendering recognizably unique textures}
+% Representing Identity 
+% %in Focus+Context Views 
+% %Hardware-Accelerated 
+% by Unique Background Textures}
 
 
 \author{
@@ -31,6 +31,19 @@
 \maketitle
 
 \begin{abstract}
+
+TJL
+
+We apply a rough, qualitative model of visual perception
+to motivate 
+general principles for designing recognizably unique textures
+for use as backgrounds for data.
+To be reconizable,
+the texture should produce a random feature vector in the brain
+{\em after} visual feature extraction. 
+
+Our motivating example is...
+
 We show how object identity can be visualized
 by
 unique background textures 
@@ -54,13 +67,6 @@
 %In Focus+Context views, the textures can act as visual cues in the context
 %(information foraging).
 
-We apply a rough, qualitative model of visual perception
-to motivate 
-general principles for designing recognizable backgrounds.
-To be reconizable,
-the texture should produce a random feature vector in the brain
-{\em after} visual feature extraction. 
-
 We discuss our freely available hardware-accelerated implementation 
 of unique backgrounds
 on the NV10 and NV25 architectures, and
@@ -110,6 +116,8 @@
 % XXX icons
 \section{Introduction}
 
+TJL
+
 ``You are in a maze of twisty 
 little passages, all alike''\cite{zork}.
 It is easy to become disoriented and lost in an environment 
@@ -194,6 +202,8 @@
 
 \section{Related work}
 
+JVK
+
 \subsection{Texturing}
 
 The {\em texture} of a surface, taken literally, is its translation-invariant 
statistical microstructure.
@@ -339,8 +349,12 @@
 
 \section{The XXX xupdf user interface --- the motivation for unique 
backgrounds}
 
+TJL
+
 \section{Unique Background Textures}
 
+TJL
+
 We define a unique background texture as an easily
 distinguishable and recognizable texture 
 that doesn't 
@@ -516,6 +530,8 @@
 
 \section{Hardware-accelerated implementation}
 
+TJL
+
 In this section, we discuss our hardware-accelerated implementation
 (libpaper)
 of unique backgrounds (papers).
@@ -914,6 +930,8 @@
 
 \section{Text readability}
 
+TJL
+
 The most commonly asked question about this work concerns 
 text readability. We address this question in two different ways.
 
@@ -933,12 +951,16 @@
 
 \section{Experiences, evaluation}
 
+JVK
+
 \section{Software availability}
 
+JVK
+
 An implementation of the unique backgrounds is available at 
-\censor{\url{http://gzz.info} as part of 
+{\url{http://gzz.info} as part of 
 the Gzz-prototype%
-}, under the GPL license.
+}, under the GPL license. XXX name change
 Fig.~\ref{figxanalogicalexample} shows the example application
 discussed in introduction running with unique backgrounds
 generated by this implementation.
@@ -956,6 +978,8 @@
 
 \section{Conclusions}
 
+TJL
+
 We have introduced procedurally generated unique backgrounds
 as a way of visualizing the identity of data.
 While the method is general and
@@ -1093,8 +1117,8 @@
 
 \section{Acknowledgments}
 
-The authors would like to thank \censor{CANNY! Benja Fallenstein and 
-Marketta Niemelä} for discussions.
+The authors would like to thank John Canny, Benja Fallenstein and 
+Marketta Niemelä and Pertti Saariluoma for discussions.
 
 
 \bibliographystyle{plain}