[Gzz-commits] manuscripts/Paper paper.tex

[Janne V. Kujala]

CVSROOT:        /cvsroot/gzz
Module name:    manuscripts
Changes by:     Janne V. Kujala <address@hidden>        03/04/25 04:39:52

Modified files:
        Paper          : paper.tex 

Log message:
        ispelling

CVSWeb URLs:
http://savannah.gnu.org/cgi-bin/viewcvs/gzz/manuscripts/Paper/paper.tex.diff?tr1=1.130&tr2=1.131&r1=text&r2=text

Patches:
Index: manuscripts/Paper/paper.tex
diff -u manuscripts/Paper/paper.tex:1.130 manuscripts/Paper/paper.tex:1.131
--- manuscripts/Paper/paper.tex:1.130   Fri Apr 25 04:15:31 2003
+++ manuscripts/Paper/paper.tex Fri Apr 25 04:39:52 2003
@@ -73,7 +73,7 @@
 
 
 %FIXME: more concise and exact explanations in some sections
-%FIXME: what are this paper's spefific contributions? (e.g., in Sec. 4)
+%FIXME: what are this paper's specific contributions? (e.g., in Sec. 4)
 
 %NO NEED FOR PERFECT RECALL - JUST A CUE
 
@@ -83,7 +83,7 @@
 We present a perceptually designed hardware-accelerated
 algorithm for generating unique background textures for distinguishing
 documents.
-To be recongizable,
+To be recognizable,
 the texture should produce a random feature vector in the brain
 after visual feature extraction. 
 
@@ -280,7 +280,7 @@
 
 %Textures have also been modeled statistically, 
 %as samples from a probability distribution on a random field.
-%The most popualar computational approach is Markov random fields
+%The most popular computational approach is Markov random fields
 %\cite{cross83markov,geman84stochastic}, 
 %where the value of each pixel
 %depends only on the values of its neighborhood (local characteristics).
@@ -336,7 +336,7 @@
 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 
+similarity to be context-dependent, making it hard to assess the 
 dimensionality.
 %% XXX: this is something we should experiment with our textures
 
@@ -350,7 +350,7 @@
 %\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 term is often used interchangeably 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).
@@ -399,7 +399,7 @@
 %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 
+%similarity to be context-dependent, making it hard to assess the 
 %dimensionality.
 %% XXX: this is something we should experiment with our textures
 
@@ -516,7 +516,7 @@
 hypertext. BuoyOING is a logical step from the earlier work
 on Fluid Links\cite{zellweger98fluid}, hypercept 
animations\cite{milgram99hypercept},
 and transpointing windows\cite{ted-xanalogical-structure-needed}.
-Buoyoing has been designed from the ground up around the following three 
principles:
+BuoyOING has been designed from the ground up around the following three 
principles:
 \begin{quote}
 \begin{enumerate}
 \item the user should always see all link targets
@@ -996,7 +996,7 @@
 % \\
 % - RGB not perceptually uniform \\
 % - Perceptually uniform color space: 
-  % distance corresponds to perceived differece of color \\
+  % distance corresponds to perceived difference of color \\
 % - Usually color perception is divided to lightness, hue, and saturation \\
 % - CIELAB\cite{cie86colorimetry}\\
 % 
@@ -1229,7 +1229,7 @@
 
 %In the following, we evaluate the implications and tradeoffs 
 %of different
-%aspects in the use of unique backround textures.  
+%aspects in the use of unique background textures.  
 
 \subsection{Overall appearance of the resulting textures}
 
@@ -1257,7 +1257,7 @@
 but only the more modest goal of zooming within a range 
 that would be reasonable for a single PDF document, 
 i.e., approximately 20-fold
-difference between mininum and maximum zoom. 
+difference between minimum and maximum zoom. 
 
 %The background textures should be be recognizable at different scales.
 Although texture perception is scale-independent to some extent,
@@ -1385,7 +1385,7 @@
 textures, we need to have an appropriate comparison point.
 Pictures of natural objects would not be appropriate,
 because they cannot be generated in infinite amounts from seed
-numbers and they would esasily yield undesirable semantic associations.
+numbers and they would easily yield undesirable semantic associations.
 Lacking a better example, we shall use plain solid color backgrounds 
 as a baseline 
 even though the colors of even a small set of randomly chosen colors would 
@@ -1429,7 +1429,7 @@
 
 Thus, we chose to measure the recognition of only 15 target textures
 or colors in the experiment. 
-Our hypthesis is that the texture backgrounds are more recognizable
+Our hypothesis is that the texture backgrounds are more recognizable
 than the solid colors.
 
 \subsubsection{Method}
@@ -1443,7 +1443,7 @@
 chosen for both the texture and solid color conditions.
 The distribution of the solid colors was the same that is used for 
 the texture colors except that the highest 
-lighness tail was de-emphasized to increase the otherwise low
+lightness tail was de-emphasized to increase the otherwise low
 discriminability of very light, unsaturated colors.
 
 \emph{Procedure.}
@@ -1532,7 +1532,7 @@
 %Our example application --- indeed, the very motivation for this work ---
 %is the focus+context view 
 %of a Xanalogical structure\cite{ted-xanalogical-structure-needed}
-%showin in Fig.~\ref{figxanalogicalexample}. For a given document,
+%shown in Fig.~\ref{figxanalogicalexample}. For a given document,
 %the view shows the fragments of other documents that
 %are linked to the current one.
 %Here, unique background textures help the user notice --- without thinking ---
@@ -1542,14 +1542,14 @@
 
 We have presented a perceptually designed hardware-accelerated
 algorithm for generating recognizably unique backgrounds.
-The motivating example, the BuoyING user interface demonstrates
+The motivating example, the BuoyOING user interface demonstrates
 that the method is at its most useful
 when the same document can be reached through
 several ways and fragments of documents are seen. 
 
 Of course, we cannot hope to match in quality a unique graphical
 appearance designed by a human designer; 
-magazines and web sites have long used skilfully designed 
+magazines and web sites have long used skillfully designed 
 graphical elements to make themselves recognizable.
 However, our algorithm is able to generate an unlimited
 amount of unique backgrounds cheaply, making it possible