[Gzz-commits] manuscripts/Paper paper.tex

[Janne V. Kujala]

CVSROOT:        /cvsroot/gzz
Module name:    manuscripts
Changes by:     Janne V. Kujala <address@hidden>        03/03/20 08:06:20

Modified files:
        Paper          : paper.tex 

Log message:
        eval

CVSWeb URLs:
http://savannah.gnu.org/cgi-bin/viewcvs/gzz/manuscripts/Paper/paper.tex.diff?tr1=1.35&tr2=1.36&r1=text&r2=text

Patches:
Index: manuscripts/Paper/paper.tex
diff -u manuscripts/Paper/paper.tex:1.35 manuscripts/Paper/paper.tex:1.36
--- manuscripts/Paper/paper.tex:1.35    Thu Mar 20 06:52:29 2003
+++ manuscripts/Paper/paper.tex Thu Mar 20 08:06:20 2003
@@ -252,8 +252,7 @@
 using 
 other textures as a starting point 
 (see, e.g., Heeger\cite{heeger95pyramid}),
-and perceptually, for visualizing surface 
orientation\cite{schweitzer83texturing}, scalar or vector 
fields\cite{ware95texture}, and
-surface shape\cite{interrante97illustrating}.
+and perceptually, for visualizing surface 
orientation\cite{schweitzer83texturing,interrante97illustrating} and scalar or 
vector fields\cite{ware95texture}.
 
 Statistical modeling of textures as samples from a probability 
 distribution on a random field as already seen in \cite{julesz62visualpattern}
@@ -1116,7 +1115,7 @@
 JVK
 
 Psychophysical studies on texture perception have mostly concentrated
-on \emph{texture discrimination}\cite{julesz62visualpattern}, 
+on \emph{visual texture discrimination}\cite{julesz62visualpattern}, 
 the ability of human observers to discriminate pairs of textures.  
 %The term is often used interchangably with \emph{texture segregation},
 %the more specific task of finding the border between differently textured 
@@ -1140,43 +1139,42 @@
 
 Julesz\cite{julesz81textons} proposed that discrimination could be explained
 by the densities of textons, fundamental texture elements, such as
-elongated blobs, line terminators, line crossings, etc.  
+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 this approach, a bank of linear filters is applied to the texture followed
+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 densities
 of 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.
 
-In our application texture discrimination is not as
+%XXX: texture perception reviews
+
+In our application visual texture discrimination is not as
 much of an issue as memorizability and recognizability of
 previously seen textures.
-Furthermore, in most texture perception work
-texture is considered as the output of a stochastic
-process that produces certain repeating features. 
-The textures created by our algorithm, although repeating, are more like 
-complete images than statistical microstructure. 
-Therefore, higher level processes of vision are also involved
-in the perception and recognition.
+The textures created by our algorithm, 
+although repeating, are more like complete images 
+than the statistical microstructure studied in most texture perception work. 
+Therefore, we also need to consider the higher level processes of vision.
 
 Experiments on black-and-white %(faces,) 
-ink blots, and snow crystals
+ink blots and snow crystals
 \cite{goldstein71visualrecognition} show that
 complex pictures can be remembered and recognized and that recognition
 performance decreases very little over time.
 
 We have conducted a pilot experiment (with one subject) 
 in a similar setting comparing
-the recognition performance of our textures with pure color backgrounds
+the recognition performance of our textures with solid color backgrounds
 (using colors from the same distribution that is used for the textures).
 First, 15 textures were shown sequentially, 5 seconds each.
 Then, recognition was tested by showing the 15 seen textures
 with 15 unseen textures in a random order, and the subject answered 
-old or new. The test was repeated with pure color backgrounds
+old or new. The test was repeated with solid color backgrounds
 for comparison.
 
 The results were as follows: 
@@ -1187,19 +1185,26 @@
 
 Of course, this result is not statistically significant,
 but in conjunction with our experiences, it suggests that the
-textures are quite recongizable and that they are clearly
-superior to pure colors in terms of recognizability.
-
-Furthermore, the experiment only measured the ability to 
-recognize previosly seen textures within unseen textures. 
-Our experience shows that
-at least the most recurring textures are not only recognized but can 
-also easily be associated with the document content.
+textures are quite recongizable while solid colors do not have
+enough variation for unambiguous recognition.
 
-- as per Zipf's law [XXXref], it suffices to learn the textures 
-  of the most recurring documents.
+The experiment measured the recognition of only 15 textures,
+and surely it would be harder to remember, e.g., 100 textures.
+However, the user does not have to remember all the textures;
+it suffices to learn the textures of the most often used documents.
+Many studies of web cache statistics 
+have shown that file popularity approximately follows Zipf's law
+(see, e.g. [xxxref]) so that a small number of documents accounts 
+for most of the use.
+Furthermore, because the texture appearance has no semantic connection 
+with the document, 
+the textures of any two important files are similar only by chance.
+
+%Our experience shows that at least the most recurring textures 
+%are not only recognized but can 
+%also easily be associated with the document content.
 
-XXX: refs?
+XXX
 
 Mapping texture appearance to an Euclidian texture space
 (see \cite{gurnsey01texturespace} and the references therein):
@@ -1215,16 +1220,7 @@
 dimensionality.
 % XXX: this is something we should experiment with our textures
 
-XXX: reviews
-
-XXX: physiological knowledge of visual perception
-(see, e.g.,~Bruce et al\cite{bruce96visualperception});
-
-theories of structural object perception 
-(see, e.g., Biederman\cite{biederman87})
-
-
-XXX
+XXX: refs?
 
 %\section{Software availability}