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revision 1.130 by jvk, Fri Apr 25 08:15:31 2003 UTC revision 1.131 by jvk, Fri Apr 25 08:39:52 2003 UTC
# Line 73  Janne V. Kujala and Tuomas J. Lukka\\ Line 73  Janne V. Kujala and Tuomas J. Lukka\\
73    
74    
75  %FIXME: more concise and exact explanations in some sections  %FIXME: more concise and exact explanations in some sections
76  %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)
77    
78  %NO NEED FOR PERFECT RECALL - JUST A CUE  %NO NEED FOR PERFECT RECALL - JUST A CUE
79    
# Line 83  Janne V. Kujala and Tuomas J. Lukka\\ Line 83  Janne V. Kujala and Tuomas J. Lukka\\
83  We present a perceptually designed hardware-accelerated  We present a perceptually designed hardware-accelerated
84  algorithm for generating unique background textures for distinguishing  algorithm for generating unique background textures for distinguishing
85  documents.  documents.
86  To be recongizable,  To be recognizable,
87  the texture should produce a random feature vector in the brain  the texture should produce a random feature vector in the brain
88  after visual feature extraction.  after visual feature extraction.
89    
# Line 280  random field\cite{cross83markov,geman84s Line 280  random field\cite{cross83markov,geman84s
280    
281  %Textures have also been modeled statistically,  %Textures have also been modeled statistically,
282  %as samples from a probability distribution on a random field.  %as samples from a probability distribution on a random field.
283  %The most popualar computational approach is Markov random fields  %The most popular computational approach is Markov random fields
284  %\cite{cross83markov,geman84stochastic},  %\cite{cross83markov,geman84stochastic},
285  %where the value of each pixel  %where the value of each pixel
286  %depends only on the values of its neighborhood (local characteristics).  %depends only on the values of its neighborhood (local characteristics).
# Line 336  However, the texture stimuli have been s Line 336  However, the texture stimuli have been s
336  For some natural texture sets,  For some natural texture sets,
337  three dimensions have also been  three dimensions have also been
338  sufficient\cite{rao96texturenaming}, but often semantic connections cause the  sufficient\cite{rao96texturenaming}, but often semantic connections cause the
339  similarity to be context-dependant, making it hard to assess the  similarity to be context-dependent, making it hard to assess the
340  dimensionality.  dimensionality.
341  %% XXX: this is something we should experiment with our textures  %% XXX: this is something we should experiment with our textures
342    
# Line 350  dimensionality. Line 350  dimensionality.
350  %\emph{visual texture discrimination}\cite{julesz62visualpattern},  %\emph{visual texture discrimination}\cite{julesz62visualpattern},
351  %the ability of human observers to effortlessly discriminate  %the ability of human observers to effortlessly discriminate
352  %pairs of certain textures (see Bergen\cite{bergen91theories} for a review).  %pairs of certain textures (see Bergen\cite{bergen91theories} for a review).
353  %%The term is often used interchangably with \emph{texture segregation},  %%The term is often used interchangeably with \emph{texture segregation},
354  %%the more specific task of finding the border between differently textured  %%the more specific task of finding the border between differently textured
355  %%areas (different phases of local characteristics at the  %%areas (different phases of local characteristics at the
356  %%border can segregate otherwise indiscriminable textures).  %%border can segregate otherwise indiscriminable textures).
# Line 399  dimensionality. Line 399  dimensionality.
399  %For some natural texture sets,  %For some natural texture sets,
400  %three dimensions have also been  %three dimensions have also been
401  %sufficient \cite{rao96texturenaming}, but often semantic connections cause the  %sufficient \cite{rao96texturenaming}, but often semantic connections cause the
402  %similarity to be context-dependant, making it hard to assess the  %similarity to be context-dependent, making it hard to assess the
403  %dimensionality.  %dimensionality.
404  %% XXX: this is something we should experiment with our textures  %% XXX: this is something we should experiment with our textures
405    
# Line 516  user interface, a focus+context interfac Line 516  user interface, a focus+context interfac
516  hypertext. BuoyOING is a logical step from the earlier work  hypertext. BuoyOING is a logical step from the earlier work
517  on Fluid Links\cite{zellweger98fluid}, hypercept animations\cite{milgram99hypercept},  on Fluid Links\cite{zellweger98fluid}, hypercept animations\cite{milgram99hypercept},
518  and transpointing windows\cite{ted-xanalogical-structure-needed}.  and transpointing windows\cite{ted-xanalogical-structure-needed}.
519  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:
520  \begin{quote}  \begin{quote}
521  \begin{enumerate}  \begin{enumerate}
522  \item the user should always see all link targets  \item the user should always see all link targets
# Line 996  chroma changes in colors. Line 996  chroma changes in colors.
996  % \\  % \\
997  % - RGB not perceptually uniform \\  % - RGB not perceptually uniform \\
998  % - Perceptually uniform color space:  % - Perceptually uniform color space:
999    % distance corresponds to perceived differece of color \\    % distance corresponds to perceived difference of color \\
1000  % - Usually color perception is divided to lightness, hue, and saturation \\  % - Usually color perception is divided to lightness, hue, and saturation \\
1001  % - CIELAB\cite{cie86colorimetry}\\  % - CIELAB\cite{cie86colorimetry}\\
1002  %  %
# Line 1229  and would require traversing the link. Line 1229  and would require traversing the link.
1229    
1230  %In the following, we evaluate the implications and tradeoffs  %In the following, we evaluate the implications and tradeoffs
1231  %of different  %of different
1232  %aspects in the use of unique backround textures.    %aspects in the use of unique background textures.  
1233    
1234  \subsection{Overall appearance of the resulting textures}  \subsection{Overall appearance of the resulting textures}
1235    
# Line 1257  with the current implementation, Line 1257  with the current implementation,
1257  but only the more modest goal of zooming within a range  but only the more modest goal of zooming within a range
1258  that would be reasonable for a single PDF document,  that would be reasonable for a single PDF document,
1259  i.e., approximately 20-fold  i.e., approximately 20-fold
1260  difference between mininum and maximum zoom.  difference between minimum and maximum zoom.
1261    
1262  %The background textures should be be recognizable at different scales.  %The background textures should be be recognizable at different scales.
1263  Although texture perception is scale-independent to some extent,  Although texture perception is scale-independent to some extent,
# Line 1385  In order to evaluate the recognizability Line 1385  In order to evaluate the recognizability
1385  textures, we need to have an appropriate comparison point.  textures, we need to have an appropriate comparison point.
1386  Pictures of natural objects would not be appropriate,  Pictures of natural objects would not be appropriate,
1387  because they cannot be generated in infinite amounts from seed  because they cannot be generated in infinite amounts from seed
1388  numbers and they would esasily yield undesirable semantic associations.  numbers and they would easily yield undesirable semantic associations.
1389  Lacking a better example, we shall use plain solid color backgrounds  Lacking a better example, we shall use plain solid color backgrounds
1390  as a baseline  as a baseline
1391  even though the colors of even a small set of randomly chosen colors would  even though the colors of even a small set of randomly chosen colors would
# Line 1429  stably from the first viewing onwards. Line 1429  stably from the first viewing onwards.
1429    
1430  Thus, we chose to measure the recognition of only 15 target textures  Thus, we chose to measure the recognition of only 15 target textures
1431  or colors in the experiment.  or colors in the experiment.
1432  Our hypthesis is that the texture backgrounds are more recognizable  Our hypothesis is that the texture backgrounds are more recognizable
1433  than the solid colors.  than the solid colors.
1434    
1435  \subsubsection{Method}  \subsubsection{Method}
# Line 1443  performed the experiment in both conditi Line 1443  performed the experiment in both conditi
1443  chosen for both the texture and solid color conditions.  chosen for both the texture and solid color conditions.
1444  The distribution of the solid colors was the same that is used for  The distribution of the solid colors was the same that is used for
1445  the texture colors except that the highest  the texture colors except that the highest
1446  lighness tail was de-emphasized to increase the otherwise low  lightness tail was de-emphasized to increase the otherwise low
1447  discriminability of very light, unsaturated colors.  discriminability of very light, unsaturated colors.
1448    
1449  \emph{Procedure.}  \emph{Procedure.}
# Line 1532  exactly what the unique background textu Line 1532  exactly what the unique background textu
1532  %Our example application --- indeed, the very motivation for this work ---  %Our example application --- indeed, the very motivation for this work ---
1533  %is the focus+context view  %is the focus+context view
1534  %of a Xanalogical structure\cite{ted-xanalogical-structure-needed}  %of a Xanalogical structure\cite{ted-xanalogical-structure-needed}
1535  %showin in Fig.~\ref{figxanalogicalexample}. For a given document,  %shown in Fig.~\ref{figxanalogicalexample}. For a given document,
1536  %the view shows the fragments of other documents that  %the view shows the fragments of other documents that
1537  %are linked to the current one.  %are linked to the current one.
1538  %Here, unique background textures help the user notice --- without thinking ---  %Here, unique background textures help the user notice --- without thinking ---
# Line 1542  exactly what the unique background textu Line 1542  exactly what the unique background textu
1542    
1543  We have presented a perceptually designed hardware-accelerated  We have presented a perceptually designed hardware-accelerated
1544  algorithm for generating recognizably unique backgrounds.  algorithm for generating recognizably unique backgrounds.
1545  The motivating example, the BuoyING user interface demonstrates  The motivating example, the BuoyOING user interface demonstrates
1546  that the method is at its most useful  that the method is at its most useful
1547  when the same document can be reached through  when the same document can be reached through
1548  several ways and fragments of documents are seen.  several ways and fragments of documents are seen.
1549    
1550  Of course, we cannot hope to match in quality a unique graphical  Of course, we cannot hope to match in quality a unique graphical
1551  appearance designed by a human designer;  appearance designed by a human designer;
1552  magazines and web sites have long used skilfully designed  magazines and web sites have long used skillfully designed
1553  graphical elements to make themselves recognizable.  graphical elements to make themselves recognizable.
1554  However, our algorithm is able to generate an unlimited  However, our algorithm is able to generate an unlimited
1555  amount of unique backgrounds cheaply, making it possible  amount of unique backgrounds cheaply, making it possible

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