Form as a Visual Encounter: Using Eye Movement
Studies for Design Reasoning
Ameya Athavankar
CEPT University, India
In spite of the architect’s interest in controlling viewer’s attention, design research
has not identified attributes that control attention as measurable and controllable
variables. Cognitive scientists, on the other hand have studied attention and shown
how variables like complexity and order can be controlled to gain and maintain
attention. This paper reports an experiment using patterns created based on
information theoretic principles and eye tracking to reveal various interrelated
insights that explain attention, visual focus and interest. It extrapolates these
findings to understand architectural forms and concludes by offering a set of
design strategies or a visual rationale for creating form.
Introduction
Of the many concerns that decisively drive the making of an architectural
form is its quality as a visual and perceptual experience. While architects
and designers are quite conscious of the quality of their visual expression,
the fact remains that this is not often acknowledged as a design problem
with a rationale of its own. Architectural criticism too has lacked
objectivity in dealing with the matter and so has been of little value in this
respect. As a consequence, most of them turn to their intuition or
experience for decisions involving judgments of visual and perceptual
quality. The situation calls for investigation of the rationale influencing
visual decisions about architectural form that enables architects to go
beyond the intuitive approach.
J.S. Gero and A.K. Goel (eds.), Design Computing and Cognition ’08,
© Springer Science + Business Media B.V. 2008
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In Search of a visual rationale
Design-related visual research has dealt with the ‘look of the environment’
or issues relating its visual form in some detail. Lynch’s study was one of
first to point out the visual importance of the environment and produced
several generic insights such as ‘imageability’ and ‘legibility’ as attributes
dealing with city form [1]. Martin Krampen reported a study conducted by
Bortz, establishing the parameters that influence ‘subjective impressions’
describing the experience of viewing building facades [2]. Another
particularly interesting study by Sanoff aimed at establishing the relation
between viewers’ judgment of ‘visual satisfaction’ with an environment
and the visual attributes influencing it [3]. Sanoff’s study emphasizes the
importance of attributes such as complexity, novelty and ambiguity in
positively influencing the judgment of visual satisfaction. The findings,
Sanoff felt, supported Berlyne’s experiments in complexity [4]. To
Berlyne, these attributes were ‘conditions leading to arousal and attention’.
His study goes a step further in establishing order and organization as
attributes that keep arousal within limits.
However, the studies treat visual attributes ‘complexity’ or ‘order’ as
discrete and undefined adjectives. Though they are insightful, the
relevance of the above studies to architectural design seems limited as they
do not point out what makes a form perceivably ‘complex’ or ‘ordered’. In
other words, these studies do not suggest a method for controlling the
attributes like ‘complexity’ or ‘order’. This limitation is rooted in the
inability to deal with these attributes as measurable properties of form. It
underscores the need for a different framework where attributes
‘complexity’ or ‘order’ may be treated as measurable properties of form
instead of discrete and undefined adjectives.
Complexity and order as measurable attributes
The information theoretic framework successfully overcomes some of the
above limitations. It treats visual attributes such as complexity and order
(as information content and redundancy) independent of the perceiver as
measurable properties of form. This is perhaps one of the main reasons for
its appeal to pattern perception. The framework also allows creating visual
patterns with attributes that may be precisely described in informational
terms. Such patterns have been used to measure the effect of complexity as
well as order in different perceptual tasks.
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Controlling complexity in visual patterns
Studies involving the use of patterns with measured complexity were
pioneered by Fred Attneave [5]. He created two dimensional `patterns
using matrices of three definite sizes (each twice the size of the previous).
In a given pattern, each cell of the matrix represented an event with two
possible outcomes: it could either contain a dot or could remain empty.
Using this technique, Attneave created two sets of patterns. In the first set
of patterns, the states of all cells of the matrix were determined
independently using a table of random numbers while the second set
contained symmetrical patterns of the same matrix sizes created simply by
reflecting one half of the patterns belonging to the first set. The complexity
of a pattern equaled the total number of cells in the matrix.
Complexity, order and memory for patterns
The patterns were then used to study viewers’ performance in three
different perceptual tasks: immediate reproduction, delayed reproduction
and identification.
The results led Attneave to conclude that constraints affect the spatial
relationships between elements and create ‘dependency’ between. This
seems to build a certain amount of predictability due to which
remembering a part of the pattern is enough to reconstruct the rest. So, in
constructing a pattern, he concluded, any visual decision (location of a dot)
that is dependent on the outcome of a previous choice or decision has an
element of ‘order’ in it. Perceivable order thus seems to manifest as
dependency among decisions while perceived visual complexity could be
seen as a relation between the two variables, the number and independence
of decisions (in locating dots) required to (re)construct a form.
Attneave’s study offers an effective method to capture ‘complexity’ and
‘order’ as measurable and controllable attributes based on the number and
independence of decisions required to (re)construct a form. Viewing
‘order’ as dependency among decisions is gives the concept greater
universality. (see Figure 1) It is possible to account for various types of
constraints (location, shape, color) as dependencies among visual events.
However, it partially helps overcome the limitations of Sanoff’s study. It
does provide a method to measure attributes of form but not reveal their
effect on attention or arousal. This understanding is of significance to
architects and designers involved in the process of architectural form
making.
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Fig. 1. Shows examples of dependent and independent decisions. In the example
on the left elements 1,2,3,4,5 share a spatial dependency while 6, 7 are spatially
independent. In the example on the right 1,2,3 are dependent shape decisions
while 4, 5 are independent shape decisions.
Research focus
There can be little doubt about the fact that there are aspects of attention
that are of importance to architects and designers. For instance, what
viewers are likely to notice or find interesting, what makes a likely
foreground and what recedes to the background significantly influence
visual expression and are questions of interest to architects. The aim of this
study is thus to measure the effect of form on attention and explore the
significance of the insights to the process of architectural form making.
This study will thus try to establish:
What in a form is likely, unlikely, or more likely to (a) evoke interest or
invite attention (b) sustain interest or retain attention. Further, what
properties of a form are likely to arouse or capture viewers’ focus and on
the other hand when do viewers show a tendency to wander?
This paper, due to reasons discussed later, uses controlled experimental
settings and stimuli. It then attempts to extend some of the insights to
present a new understanding of architectural forms and visual strategies
employed by architects to achieve some of the objectives discussed above.
Experimental approach: Attention and eye-behavior
The studies cited earlier use instruments such as semantic differential for
recording descriptive responses to visual environments. This study takes a
similar experimental route to seek the answers to the above questions.
However, as opposed to the above studies, it ensures greater objectivity by:
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• Studying eye movements instead of relying on verbal judgments
• Using forms with controlled and measurable attributes as stimuli.
Eye movements have been considered by researchers to be an ‘overt
behavioral manifestation’ of visual attention [6]. Besides, technological
developments in eye tracking have made it possible to record and precisely
measure and study various characteristics of eye movements. Although its
early use was restricted to fields such as psychology and human factors, in
recent times eye tracking has found several other applications in many
areas of visual research. These include reading, human computer
interaction, advertising, visual art and films [7].
The experimental approach involves isolating visual characteristics of
form and capturing them in a set of non-representational forms as
controlled and measurable attributes. It proceeds to seek differences in eye
movement responses to these forms so as to reveal the effect of measured
changes in attributes. The insights or principles derived from the
experiment are then extrapolated to understand architectural forms that are
difficult to measure.
Although more direct insights could have been obtained by recording
viewers’ eye movements in actual settings, available eye tracking
instruments did not allow for this. Also, as research has shown that eyebehavior in the real world is influenced not only by visual but also
semantic characteristics and familiarity or prior knowledge of a scene
[8].The interaction of visual and semantic characteristics also poses other
difficulties. This became apparent in initial experiments that used
photographic representations of building facades and seemed to reduce
objectivity in interpreting eye movement data. As would be of interest to
architects and designers in particular, it was decided to focus on studying
visual (or structural) characteristics of form or its pre-meaning perception.
It is true that semantics is likely to significantly influence not only eyebehavior but also the ‘look’ of an architectural form. However, it may be
argued that its role is restricted to providing an overall governing visual
framework. It is unlikely to greatly influence architects’ local visual
decisions about form and the effect of this on visual attention cannot be
denied. This study focuses only on establishing visual attributes and their
role in influencing attention. In spite of the effect of semantics or prior
knowledge, such understanding continues to hold valuable insights for
architects. This, in no way implies that it underrates the influence of these
factors. It merely attempts to serve as a pilot enquiry and must be seen as a
starting point for studying various aspects of attention and its implications
to design.
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Experimental design
In order to focus on visual attributes (and eliminate semantics) nine nonrepresentational patterns were created based on the information theoretic
principles used by Attneave [1], [9]. As in Attneave’s study, differential
complexity and order were created through measured changes in variables
matrix size (number of elements) and spatial independence of elements.
Constructing sample patterns
The visual field or display of 4:3 (1024x768) was assumed to consist of
matrices of the same proportions. The sizes of matrices were fixed at three
different levels: 48 (8x6), 192 (16x12) or 768 (32x24) cells. Each cell of
the matrix represented an event with two possible outcomes. It could either
be blank or could contain a dot. The overall probability or the total number
of dots in a pattern was fixed at 1/4 (12 dots), 1/8 (24 dots) and 1/16 (48
dots) for the three levels. To begin with positions of dots were fixed in a
regular or homogeneous arrangement to create three patterns (S11, S21,
S31). These patterns were then reproduced with 25 percent, (S12, S22,
S32) and 50 percent (S13, S23, S33) displacements in the dot-positions
using a random number generator. The result was a set of nine sample
patterns with three different levels of matrix size and three degrees of
spatial independence of elements. (see Figure 2)
Procedure
The nine patterns were mixed with five similar patterns and shown to 8
viewers while their eye movements were recorded. All the viewers
belonged to the age group 20-30 years and were found to be naïve to the
purpose of the experiment. The sequence and timing of slides containing
patterns was controlled by ‘Presentation v11’ software. Viewers were
instructed to themselves control the viewing duration through a response
key.
Setup
The experimental setup consisted of two computers: the subject system (a
Pentium V with a 72 dpi 13” LCD monitor set to 1024x768) used for
displaying the patterns and the operator system (SMI’s REDIII and
iViewX system) for recording eye movements. The subject’s monitor was
placed at 900mm from the chin support. The REDIII is a contact-free and
non-intrusive device which views the subject from a distance.
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Fig. 2. Shows the analytical scheme for comparing trends in values for all five
measures to reveal the independent and interactive effect of the variables.
Scheme for analytical treatment of eye movement data
Eye movement data was processed and analyzed using SMI’s BeGaze
v1.2.76. The software was used to visualize eye movements as scanpaths
and attention maps as well as to identify and log fixation and saccadic data.
To systematically study the independent and interactive effect of each
variable, an analytical scheme was created. The set of nine sample patterns
can be arranged in a 3x3 arrangement (see Figure 2) where:
1. The rows contain patterns with the same degree of spatial
independence, but show an increase in the matrix size and number of
elements from left to right while the columns contain patterns with
same matrix size and number of elements, but show an increase in the
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degree of spatial independence from top to bottom. So, row-wise and
column-wise comparisons of data reveal the independent effects of
increase in matrix size or number of elements and spatial
independence. For eg. S11, S21, S31 and S11, S12, S13.
2. Patterns located along:
a.The right diagonal (connecting the top-left to the bottom-right corner)
shows an increase in number as well as spatial independence of
elements. For eg. S11, S22, S33.
b. The left diagonal (connecting the bottom-left to the top-right corner)
shows an increase in number but a decrease in spatial independence
of elements. For eg. S13, 22, 33.
Comparison of data along the right and the left diagonal with the data
along the rows and columns reveals interactive effects of variables.
Scope and limitations of the analysis
A search revealed no previous instances of the use of eye tracking for
purposes similar to this study. As a pilot, the study had the added task of
establishing measures capable of capturing relevant changes in
characteristics of eye movements in response to changes in attributes. This
was an effort intensive task involving a breadth-first survey of many more
measures than presented here. Importantly it created two limitations:
• Eye movements of a limited sample of 8 viewers could be considered.
• Small sample of 9 patterns could be used.
A set of 9 patterns are unlikely to yield totally consistent patterns across
8 viewers. The analysis was directed to making broad categorical
inferences such as relative increase or decrease rather than making detailed
enquires into actual quantities or degrees of change. It was restricted to
comparing and observing trends in mean values calculated from data
obtained over 8 viewers consistent with the analytical scheme for a variety
of measures.
The small sample size of viewers ruled out the possibility of testing the
results for their statistical significance or conducting an ANOVA. The
limited number of sample patterns also had its implications. It may be
recalled that the patterns were created using a random number generator.
This method can sometimes result in unexpected, yet strong local grouping
or Gestalts. Such grouping produced some inconsistencies, visible in the
data. Ideally, as in case of Attneave’s study the effect of such grouping
should have been eliminated by considering a large number of samples of a
pattern [1]. However, increasing the number of patterns would not only
have stressed viewers but also produced an enormous amount of eye
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movement data. Processing data for a large number of measures would be
much beyond the scope of the study.
The conclusions of the study will thus be speculative and at times
tentative in tone. They must be seen as initial findings that are in need of
further study. However, the results seem promising and yield interesting
insights into form and visual attention. Therefore are considered worth
sharing.
Interpreting eye-behavior
A discussion on concepts of eye movements has been avoided here, for
reasons of economy. Those interested in deeper understanding may want to
refer to Yarbus’s or Duchowski’s book for a fascinating account of theory
as well as applications of eye tracking [10], [7]. The results have been
discussed in relation to the aims of the study so as to enable an assessment
of whether the study has succeeded in answering the questions that were
raised earlier.
Evoking visual interest
One of the questions the study aimed to answer dealt with the ‘foregroundness’ of the entire group of dots or elements as a whole and their ability to
evoke visual interest. It was framed as: What in a form is likely, unlikely,
or more likely to evoke interest or invite attention? This section deals with
the question in detail.
Fixations: Number and locations
Ratio of on-target fixations (Preferred fixation sites): The ratio of on-target
fixations compares the number of fixations received by the entire group of
elements (cells with dots) to the total number of fixations received by the
pattern. It captures viewers’ preference for fixation sites.
Significance: In a pattern, elements (as a whole) receiving more
fixations relative to the background must have greater collective ability to
evoke visual interest and therefore a greater foreground-ness as compared
to those receiving fewer fixations. This collective ability among elements
can be captured by the ratio of on-target fixations.
In usability research, ratio of on-target fixations has been used to
determine the efficiency of scanning behavior [11]. Considering the
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differences in experimental task, its use and interpretation have been
suitably modified in this study.
Ratio of elements-hit or hit-rate (Chance of an element being fixated):
The hit-rate compares the number of elements-fixated to the total number
of elements in the pattern. It captures the overall chance of an element
being fixated.
Significance: An element with a higher chance of receiving a fixation
must belong to a group that evokes more visual interest as compared one
where fewer elements receive fixations. This individual ability among
elements can be captured by the ratio of elements-hit (fixated) or the hitrate.
Independent and interactive effects
The effects of the variables on the measures (see Figure 3) are as follows:
Independent Effects: The (a) ratio of on-target fixations (b) hit-rate
seems to increase as the spatial independence of elements increases and
decreases when the number of elements increases.
Insight: Increased spatial independence among elements seems to
improve their collective and individual ability to evoke visual interest
while addition of elements seems to marginally diminish it.
Interactive Effects: The (a) ratio of on-target fixations (b) hit-rate seems
to marginally decrease along the right diagonal. The decrease is less than
the independent effect of increase in number of elements.The (a) ratio of
on-target fixations (b) hit-rate seems to sharply decrease along the left
diagonal. The decrease is more than the independent effect of either
variable.
Insight: Reduction in the collective and individual ability of elements to
evoke visual interest due to a four fold increase in the number of elements
may partially be balanced by a 50 percent increase in spatial independence.
Insight: Increasing the degree of spatial independence and reducing the
number of elements seems to severely diminish their collective and
individual ability to evoke visual interest.
Consolidated insights
Due to commonalities in content as well as to enable a better comparison,
the insights presented above will be discussed in 3.3.3.
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Sustaining visual interest
The ‘foreground-ness’ of a group of elements cannot be fully studied
without establishing what influences the ability of elements to sustain
visual interest. One of the questions the study aims to answer was framed
as: What in a form is likely, unlikely, or more likely to sustain interest or
retain attention? This section will discuss the question is detail.
Fixations: Duration and location
Relative fixation time (Share of Fixation time): Relative fixation time
compares time spent by viewers fixating elements to the time spent
fixating on the entire pattern. It captures the share of fixation time received
by elements.
Significance: A group of elements (as a whole) receiving a larger share
of fixation time must have a greater ability to sustain visual interest
compared to those receiving a relatively smaller share. This collective
ability among elements may be captured by relative fixation time.
Cumulative or total fixation time spent within a certain area of the
image in usability studies is interpreted as the amount of interest shown by
viewers [12]. However, considering the experimental design here, it was
necessary to neutralize the effect of differential viewing time. The
cumulative fixation time (on elements) was measured relative to the total
fixation time for the pattern.
Fixation time per element-hit (Dwell time over a fixated element): The
fixation time per element-hit compares the total fixation time spent over
elements to the number of elements fixated. It captures how much viewers
dwelt over an element.
Significance: An individual element on which fixations dwell more,
arguably, sustains more visual interest compared to one on which they
dwell less. This ability among individual elements may be captured by the
fixation time per element-hit.
Independent and interactive effects
The effect of the variables on the measures (see Figure 4) is as follows:
Independent Effects: The (a) relative fixation time seems to increase (b)
fixation time per element-hit seems to increase when the spatial
independence of elements is increased. The (a) relative fixation time seems
to increase (b) fixation time per element-hit seems to increase when the
number of elements is increased.
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Fig. 3. Shows values of ratio of on-target fixations (ot) and hit-rate (hr) for all nine
patterns and typical eye-scanpaths for selected patterns. Note how elements (dots)
in patterns S13 and S33 pull attention towards themselves with large saccadic
movements while elements in patterns S11 or S31 cease to do so. Also note that
the scanpaths shown above are typical examples and may not be consistent with
actual mean data.
Insight: Increased spatial independence seems to improve the collective
and individual ability of elements to sustain visual interest.
Insight: Addition of elements seems to improve the collective ability but
diminishes the individual ability of elements to sustain interest.
Interactive Effects: The (a) relative fixation time seems to sharply
increase (b) fixation time per element-hit seems to marginally decrease
along the right diagonal. The increase in relative fixation time is greater
than the independent effect of either variable. The decrease in fixation time
per element-hit is less than independent effect of increase in number of
elements.
The (a) relative fixation time seems to marginally decrease (b) fixation
time per element-hit seems to sharply decrease along the left diagonal. The
decrease in relative fixation time is lesser than the independent effect of
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spatial independence. The decrease in fixation time per element-hit is
greater than independent effect of either variable.
Insight: Increasing the number and the degree of spatial independence
of elements seems to improve their collective ability to sustain visual
interest.
Insight: Reduction in the ability of individual elements to evoke visual
interest due to a four fold increase in the number of elements may partially
be balanced by a 50 percent increase in spatial independence.
Insight: Reduction in the collective ability of elements to sustain visual
interest due to a 50 percent increase in spatial independence may partially
be balanced by four fold increase in number.
Insight: Increasing the degree of spatial independence and reducing the
number of elements seems to improve their individual ability to sustain
visual interest.
Consolidated insights
The ability to evoke (invite attention) and sustain visual interest (retain
attention) seems to be strongly related to the spatial independence of
elements. Spatial independence creates uniqueness in inter-element
relationships and unpredictability the relative positions of elements. This is
what possibly improves their collective as well as individual ability to
evoke and sustain interest.
Addition of elements, on the other hand seems to have an interesting
effect. As one would expect more elements in a pattern competing for
attention diminishes the ability of an individual element to evoke or sustain
visual interest. Surprisingly, addition of elements does not seem to
improve the collective ability of a group of elements to evoke visual
interest or invite attention but it does help them sustain interest or retain
attention.
Capturing visual focus
One of the questions that the study aims to answer concerns the ability
capture visual focus. It was framed as: What properties of a form are likely
to arouse or capture viewers’ focus and on the other hand when do viewers
show a tendency to wander? This section deals with the question in detail.
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Fixation time: Spatial distribution
Ratio of Fixation/ Saccadic time (Distribution of fixation time): The ratio
of fixation to saccadic time compares the time spent by viewers (in
fixation) acquiring information from the pattern to the time spent searching
for it (through saccades). A higher fixation/saccadic time indicates that
fixation time was concentrated and fixations were retained in fewer
locations about the pattern, while a lower value implies that fixations were
short and scattered over many locations separated by saccadic search for
these locations.
Fig. 4. Shows values of ratio of relative fixation time (rf) and fixation time per
element-hit (fe) for all nine patterns and typical eye-scanpaths for selected
patterns. Note how elements (dots) in patterns S13 and S33 receive more as well
as longer fixations (larger circles) while elements in patterns S11 or S31 receive
fewer and shorter fixations (smaller circles) Also note that the scanpaths shown
above are typical examples and may not be consistent with mean data presented.
Significance: It may be argued that a pattern likely to capture visual
focus must produce focused or directed scanning. On the other hand, a
pattern unlikely to capture focus or one that divides or distributes focus
may produce a wandering tendency in scanning. This should be reflected
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in the spatial distribution of fixation time (sparse or concentrated) and may
best be captured by the ratio of fixation/ saccadic time.
In usability research this measure has been used to determine the search
efficiency, since it compares time spent by viewers acquiring and
processing information to the time spent locating it [11]. Its use and
interpretation here have been modified to suit the requirements of this
study.
Independent and interactive effects
The effects of variables on the measures (see Figure 5) are as follows:
Independent Effects: The ratio of fixation/ saccadic time seems to
increase when spatial independence among elements is increased and
decreases when their number is increased.
Insight: Increased spatial independence seems to capture visual focus
while addition of elements seems to divide and distribute it resulting in a
wandering tendency.
Interactive Effects: The ratio of fixation/ saccadic time seems to
marginally increase along the right diagonal. The increase is less than the
independent effect of spatial independence. The ratio of fixation/ saccadic
time seems to sharply decrease along the left diagonal. The decrease is less
than the independent effect of either variable.
Insight: Reduction in the ability to capture visual focus due to a four
fold increase in number of elements may be partially balanced by a 50
percent increase in spatial independence.
Insight: Increasing the number of elements and reducing the degree of
spatial independence seems to least capture focus resulting in the highest
tendency to wander.
Consolidated insights
The ability (or inability) in a pattern to capture viewers’ focus seems to be
strongly influenced by the spatial independence of elements. Increasing the
degree of spatial independence seems to break homogeneity of a pattern. It
creates unique and unpredictable grouping among elements and a
hierarchy among regions. This characteristic seems to be decisively
influence for the ability to capture focus. Addition of elements, on the
other hand seems to have quite the opposite effect. More elements seem to
create more groups. This seems to taper the hierarchy, dividing and
distributing it among more regions. It is however possible to counter the
reduction in the ability to capture focus by proportionately increasing the
degree of spatial independence of elements.
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Attention vs. memory for patterns
The insights listed above are particularly interesting when seen in relation
to Attneave’s findings on viewers’ performances in memory tasks. His
study attributes learning difficulty to the independence of decisions
(locating elements) required to (re)construct a pattern. The findings
discussed in the previous sections also continually emphasize the decisive
influence of independence of elements (or decisions), on the ability to
evoke and sustain visual interest or capture visual focus. (see Figure 6) It
seems that some of the characteristics of a pattern that help elicit a strong
visual response, also seem to make it more difficult to memorize.
Fig. 5. Shows the values of ratio of fixation/ saccadic time (f/s) for all nine
patterns and typical attention maps for selected patterns. Attention maps indicate
the distribution of fixation time about a pattern. It is represented as a color
gradient from violet (relatively less fixation time) to red (relatively more fixation
time). Note how pattern S13 shows a dense distribution while S31 shows a
scattered distribution. Also note that the attention maps shown are typical
examples and do not represent mean data.
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Relevance to architects and designers
This paper attempts to understand the relationship between form-attributes
and visual attention through the analysis of eye-behavior. Using abstract
patterns (with controlled attributes) it establishes principles that influence
attention and arousal. In the sections that follow, an attempt is made to
extend some of the ideas to create a different understanding of
architectural form. With further research some of these ideas could also be
developed as a design tool. In the near future eye trackers are likely to
become increasing portable and possibly ubiquitous. This should enable
direct use of eye tracking to deal with some of the issues addressed here.
However, at this point of time laboratory route seems the best available
option in terms of the ability to isolate and control attributes as well as
objectively analyze eye movement data.
Insights as principles for architectural form-making
There is no doubt about the fact that controlling viewers’ attention is one
of the unstated objectives of an architect. It is not uncommon, for instance
to find an architect or a designer taking special efforts to ensure that his
form or its features capture the interest of viewers or so that their attention
may linger on it more than what is functionally adequate. In other cases, he
may wish that viewers do not notice a form or some of its features at all.
He also hopes that they retain a certain memory of his form. The insights
and findings presented here can be developed as visual strategies that
could be employed by a designer to achieve some of these objectives.
Interestingly, the variables (number and spatial independence of
elements) to some extent represent real visual situations that architects
often encounter. For instance, an architect or designer may be confronted
with the problem of creating entrances, displays or signage that must
capture viewers’ focus in settings such as commercial streets, airports,
train terminals or shopping malls, where a large number of visual elements
compete for viewers’ attention. In other cases, he may be expected to
design a showroom that not only evokes but also sustains interest. On the
other hand, highway signage, advertisements or displays as instances
where viewers do not have the luxury of too much viewing time. After all,
influencing attention is his first essential step in establishing
communication with viewers.
It must be noted that the perceived effect of form cannot be judged
merely based on its ability to capture focus or invite and sustain interest.
As Berlyne stated, an ‘aesthetic product’ is one that not only gains and
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maintains the attention of the audience but also keeps arousal within limits
[13]. Balancing of complexity and order in a message has always been
critical in any communication. After all features which do not capture
focus or interest that make time and attention available to those which do.
The insights presented earlier allow a designer to carefully plan the
perceived hierarchy within the features of his form influencing what is
likely to capture focus and what is not.
Fig. 6. Shows changes in scanpath characteristics due to the effect of measured
changes in number of elements and spatial independence.
The concept of ‘visual space’
The true significance of the work is in the creative use of the insights
presented in the earlier sections to develop a deeper understanding of
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process of creating forms going beyond the current intuitive approach. The
relationships between insights can be exploited to convert them into
overall visual strategies that architects can use to predictably influence
visual response. To facilitate this relationships between insights, the spatial
arrangement of (nine) patterns can be visualized as a continuous and
limitless ‘visual space’ where attributes can be treated as controllable
variables. (see Figure 7) The perceived effect of a form can be establishing
through its position in visual space.
Fig. 7. Shows a representation of the ‘visual space’ and how built forms may take
up different positions on it. The examples presented are (clockwise) German
Pavillion at Barcelona, Lake Shore Drive Apartments at Chicago, Guggenheim
Museum at Bilbao, Notre-Dame-du-Haut at Ronchamp.
The visual space can serve as an effective analytical tool for
understanding architectural forms. Positioning carefully chosen forms in
the space can reveal interesting visual strategies employed by a particular
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A. Athavankar
architect or designer or during a particular time period or region etc. A
preliminary attempt in this direction has been made here, by relatively
placing renowned architectural forms in selected positions of the space.
(see Figure 7) It seems to yield promising insights.
With further research the visual space may be developed as a design tool
with that can account for many more variables and reflect the actual
complexity of architectural forms. This should allow an architect to
position his form (or its different features) and predict the relative effect on
visual interest, focus and learning difficulty. Architects can use the space
for reasoning and taking visual decisions.
The contention of the paper is that among its other roles, architectural
form is something to be seen. It must be designed as a deliberate and
designed encounter leading to an active and engaging visual dialogue. The
ability to influence viewers’ attention is an important first step in doing so.
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