Washington University in St. Louis
Washington University Open Scholarship
All Computer Science and Engineering Research
Computer Science and Engineering
Report Number: WUCSE-2007-18
2007
The Effect of Object Color on Depth Ordering
Authors: Reynold Bailey, Cindy Grimm, Christopher Davoli, and Richard Abrams
The relationship between color and perceived depth for realistic, colored objects with varying shading was
explored. Background: Studies have shown that warm-colored stimuli tend to appear nearer in depth than
cool-colored stimuli. The majority of these studies asked human observers to view physically equidistant,
colored stimuli and compare them for relative depth. However, in most cases, the stimuli presented were
rather simple: straight colored lines, uniform color patches, point light sources, or symmetrical objects with
uniform shading. Additionally, the colors were typically highly saturated. Although such stimuli are useful for
isolating and studying depth cues in certain contexts, they leave open the question of whether the human
visual system operates similarly for realistic objects. Method: Participants were presented with all possible
pairs from a set of differently colored objects and were asked to select the object in each pair that appears
closest to them. The objects were presented on a standard computer screen, against 4 different uniform
backgrounds of varying intensity. Results: Our results show that the relative strength of color as a depth...
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Bailey, Reynold; Grimm, Cindy; Davoli, Christopher; and Abrams, Richard, "The Effect of Object Color on Depth Ordering" Report
Number: WUCSE-2007-18 (2007). All Computer Science and Engineering Research.
http://openscholarship.wustl.edu/cse_research/122
Department of Computer Science & Engineering - Washington University in St. Louis
Campus Box 1045 - St. Louis, MO - 63130 - ph: (314) 935-6160.
The Effect of Object Color on Depth Ordering
Complete Abstract:
The relationship between color and perceived depth for realistic, colored objects with varying shading was
explored. Background: Studies have shown that warm-colored stimuli tend to appear nearer in depth than
cool-colored stimuli. The majority of these studies asked human observers to view physically equidistant,
colored stimuli and compare them for relative depth. However, in most cases, the stimuli presented were
rather simple: straight colored lines, uniform color patches, point light sources, or symmetrical objects with
uniform shading. Additionally, the colors were typically highly saturated. Although such stimuli are useful for
isolating and studying depth cues in certain contexts, they leave open the question of whether the human
visual system operates similarly for realistic objects. Method: Participants were presented with all possible
pairs from a set of differently colored objects and were asked to select the object in each pair that appears
closest to them. The objects were presented on a standard computer screen, against 4 different uniform
backgrounds of varying intensity. Results: Our results show that the relative strength of color as a depth cue
increases when the colored stimuli are presented against darker backgrounds and decreases when presented
against lighter backgrounds. Conclusion: Color does impact our depth perception even though it is a relatively
weak indicator and is not necessarily the overriding depth cue for complex, realistic objects. Application: Our
observations can be used to guide the selection of color to enhance the perceived depth of objects presented
on traditional display devices and newer immersive virtual environments.
This technical report is available at Washington University Open Scholarship: http://openscholarship.wustl.edu/cse_research/122
Department of Computer Science & Engineering
2007-18
The Effect of Object Color on Depth Ordering
Authors: Reynold Bailey, Cindy Grimm, Christopher Davoli, Richard Abrams
Corresponding Author: rjb1@cse.wustl.edu
Abstract: The relationship between color and perceived depth for realistic, colored objects with varying shading
was explored. Background: Studies have shown that warm-colored stimuli tend to appear nearer in depth than
cool-colored stimuli. The majority of these studies asked human observers to view physically equidistant,
colored stimuli and compare them for relative depth. However, in most cases, the stimuli presented were rather
simple: straight colored lines, uniform color patches, point light sources, or symmetrical objects with uniform
shading. Additionally, the colors were typically highly saturated. Although such stimuli are useful for isolating and
studying depth cues in certain contexts, they leave open the question of whether the human visual system
operates similarly for realistic objects. Method: Participants were presented with all possible pairs from a set of
differently colored objects and were asked to select the object in each pair that appears closest to them. The
objects were presented on a standard computer screen, against 4 different uniform backgrounds of varying
intensity. Results: Our results show that the relative strength of color as a depth cue increases when the colored
stimuli are presented against darker backgrounds and decreases when presented against lighter backgrounds.
Conclusion: Color does impact our depth perception even though it is a relatively weak indicator and is not
necessarily the overriding depth cue for complex, realistic objects. Application: Our observations can be used to
Type of Report: Other
Department of Computer Science & Engineering - Washington University in St. Louis
Campus Box 1045 - St. Louis, MO - 63130 - ph: (314) 935-6160
Depth by Color
1
Running head: OBJECT COLOR ON DEPTH ORDERING
THE EFFECT OF OBJECT COLOR ON DEPTH ORDERING
REYNOLD J. BAILEY,1 CINDY M. GRIMM,1 CHRISTOPHER C. DAVOLI,2 and
RICHARD A. ABRAMS2
1
Washington University in St. Louis, Department of Computer Science and Engineering,
St. Louis, Missouri, USA
2
Washington University in St. Louis, Department of Psychology,
St. Louis, Missouri, USA
Address correspondence to:
Reynold J. Bailey
Department of Computer Science and Engineering
Campus Box 1045
Washington University in St. Louis
St. Louis, MO, 63130
Email: rjb1@cse.wustl.edu
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Abstract
Objective: The relationship between color and perceived depth for realistic, colored
objects with varying shading was explored. Background: Studies have shown that warmcolored stimuli tend to appear nearer in depth than cool-colored stimuli. The majority of
these studies asked human observers to view physically equidistant, colored stimuli and
compare them for relative depth. However, in most cases, the stimuli presented were
rather simple: straight colored lines, uniform color patches, point light sources, or
symmetrical objects with uniform shading. Additionally, the colors were typically highly
saturated. Although such stimuli are useful for isolating and studying depth cues in
certain contexts, they leave open the question of whether the human visual system
operates similarly for realistic objects. Method: Participants were presented with all
possible pairs from a set of differently colored objects and were asked to select the object
in each pair that appears closest to them. The objects were presented on a standard
computer screen, against 4 different uniform backgrounds of varying intensity. Results:
Our results show that the relative strength of color as a depth cue increases when the
colored stimuli are presented against darker backgrounds and decreases when presented
against lighter backgrounds. Conclusion: Color does impact our depth perception even
though it is a relatively weak indicator and is not necessarily the overriding depth cue for
complex, realistic objects. Application: Our observations can be used to guide the
selection of color to enhance the perceived depth of objects presented on traditional
display devices and newer immersive virtual environments.
Depth by Color
3
THE EFFECT OF OBJECT COLOR ON DEPTH ORDERING
Various sources of information in a scene contribute to our perception of depth.
These sources are referred to as depth cues and are typically grouped into three
categories: pictorial, occulomotor and stereo cues (Gillam, 1995). Pictorial depth cues are
ones that we obtain from two-dimensional images. These include information such as
relative size, distance to horizon, focus, occlusion, shadows, shading, relative brightness,
atmospheric effects, and color (Pfautz, 2000). Perspective cues such as relative size,
occlusion, and distance to the horizon are generally more effective at conveying depth
than shading, luminance, and color (Hone & Davis, 1993; Surdick et al., 1994; Wanger,
Ferwerda, & Greenberg, 1992).
Although color is considered to be one of the weaker depth cues, its impact on
depth perception has been studied extensively by psychologists and other vision
researchers. Artists and designers refer to colors that appear closer to the red end of the
visible spectrum as warm colors, and colors that appear closer to the blue end as cool
colors.1 Early references to the color-depth relationship in literature refer to reds and
oranges as advancing colors and blues as receding colors or retiring colors (Goethe,
1810/1982; Luckiesh, 1918). The actual experimental study of the effect of color on
perceived depth began in latter half of the 19th century (see Payne, 1964 and Sundet, 1978
for summaries). In most of these studies, different colored stimuli were presented to
human observers and their depth preferences were recorded. It was generally observed
that warmer colors tend to appear closer to the viewer than cooler colors.
In order to account for these observed depth differences, several theories that are
based on the physiology of the human visual system have been proposed. For example, it
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4
has been observed that the color sensitive cones in the retina exhibit a slight bias
(stronger responses) to colors toward the warm end of the visible spectrum (see Figure
1a). Some physiologists have suggested that this bias may be strong enough to result in
perceived depth differences between colors (Livingstone, 2002).
Another (more accepted) theory states that the difference in perceived depth is
due to the fact that shorter wavelengths of visible light are refracted more than longer
wavelengths (Sundet, 1978). As a result, equidistant sources of differing wavelengths
cannot be simultaneously focused onto the retina by the eye's optical system. This is
referred to as chromatic aberration and is illustrated in Figure 1b.
A review of the research literature on color-depth experiments (and in fact most
depth-cue experiments) reveals that in most cases the stimuli presented were very simple.
The stimuli generally consisted of straight colored lines, uniform color patches, point
light sources, or symmetrical objects with uniform shading. Additionally, the colors used
were typically highly saturated.
There are two main reasons for the use of such simple stimuli. First, many early
researchers used the weak observer theory (Landy, Maloney, Johnston, & Young, 1995)
as a basis for their experiments. This theory suggests that the various depth cues are
processed by the visual system independently of each other and our final overall depth
perception is simply a weighted combination of the contribution of the individual depth
cues. Additionally, while most modern researchers quickly dismiss this theory, it is
difficult to design effective experiments for the alternative strong observer theory
(Doorschot, Kappers, & Koenderink, 2001; Guibal & Dresp, 2004; Landy et al., 1995).
The strong observer theory suggests that there are complex interactions between the
Depth by Color
5
various depth cues. The presence of one or more depth cues may either enhance or
suppress the effect of other cues. Secondly, the use of simple stimuli by early researchers
can be attributed to the lack of computing power, display technology, and accurate
measuring devices. While simple stimuli are useful in isolating and studying depth cues
in certain contexts, they leave open the question of whether the human visual system
operates similarly for realistic objects.
The knowledge gained from the study of human depth perception has been used
by computer graphics researchers to develop techniques for manipulating the apparent
depth of objects in computer-generated scenes. These techniques typically rely on threedimensional representations of the scene where depth information is readily available.
Examples include the introduction of atmospheric effects like haze or fog (Woo, Neider,
Davis, & Shreiner, 1999), perspective changes such as the shape, size, or position of
objects (or camera) (Foley, van Dam, Feiner, & Hughes, 1996) and level of detail (LOD)
changes (Heckbert & Garland, 1994). In the case of images, where a 3D representation of
the scene is not available, Gooch and Gooch (2004) have shown that the perceived depth
can be enhanced by adding an artistic matting. More recently, Bailey and Grimm (2006)
have shown how subtle apparent depth changes can be introduced by manipulating either
the luminance or color of the object and/or background. The results of the experiment
presented in this paper can be used to guide the selection of color to further enhance the
perceived depth of objects presented on traditional display devices and newer immersive
virtual environments.
This experiment was designed to explore the effect of color on perceived depth
for a realistic colored object with varying shading and contours. Participants were
Depth by Color
6
presented with all possible pairs from a set of differently colored objects and were asked
to select the object in each pair that appears closest to them. This approach is called a
paired comparison test. Ledda, Chalmers, Troscianko, and Seetzen (2005) present a
strong case for the use of this type of testing. Although the number of test pairs (and
hence experiment time) grows quickly as the number of objects in the test set increases,
they point out that the results of a paired comparison test do not suffer from the distortion
that is common in ranking or rating approaches (Siegel & Castellan, 1988). The objects
were presented against 4 different uniform backgrounds of varying intensity levels. This
allows us to analyze the impact of luminance contrast on the depth preferences recorded.
METHOD
Participants
Fifteen students (4 females, 11 males), between the ages of 18 and 40 volunteered
to participate in this study. They all reported normal or corrected-to-normal vision with
no color vision abnormalities.
Stimuli
Stimuli were presented on a 17 inch monitor, operating at 60 Hz with a resolution
of 1280 x 1024. The stimuli used in this experiment consisted of images of 7 colored
teapots and 7 uniform colored patches. To create the stimuli, we began with a photograph
of a teapot2 (see Figure 2a) and performed segmentation using an interactive min-cut
max-flow segmentation algorithm proposed by Boykov and Jolly (2001). Seven
perceptually distinct colors were manually selected (see Figure 2b). The luminance of
these colors was adjusted to match the average luminance of the original teapot. The
resulting equiluminant colors are shown in Figure 2c. Each of these target colors was
Depth by Color
7
then applied to the teapot. This was done by scaling the target colors by the pixel
luminance values of the original teapot. This approach preserves the shading and specular
highlights of the original teapot (see Figure 3a). The 7 colored uniform patches were
simply images of each of the equiluminant target colors (see Figure 3b). Each teapot
image and each color patch image subtended a visual angle of 5o (i.e. 5o high and 5o
wide).
Procedure and Design
Participants were seated in front of a computer screen in a dimly lit room. Two
differently colored objects of the same type (teapot or color patch) were presented on
screen for each trial. The objects were displayed on either side of an imaginary central
line on the screen. The background for both objects in a single trial could be one of the
four different uniform levels of gray, evenly spaced from black to white. Participants
were instructed to decide which object appeared nearer and responded by moving the
mouse over their choice and clicking on it. If participants were unsure, they were
instructed to choose based on their initial impulse. Participant response time for each trial
was also recorded. Between each trial, a blank screen was displayed for 2 seconds. This
was done because it has been shown that our perception of depth diminishes with viewing
time (Troscianko, Montagnon, Le Clerc, Malbert, & Chanteau, 1991). A 2 second
interval prevents total adaptation, thereby ensuring that depth perception remains stable
(Troscianko et al., 1991). Each participant performed 21 comparisons for each type of
object against each of the 4 possible backgrounds, for a total of 168 experimental trials.
An object of a particular color was never compared against itself, but all other withinobject color comparisons occurred. All trials that fell under one type of object and one
Depth by Color
8
type of background comprised a block, for a total of eight blocks (i.e. teapots presented
against each of the 4 backgrounds, and color patches presented against each of the 4
backgrounds). The presentation order of the blocks was randomly determined and trials
within each block were randomly ordered. It was randomly determined for each trial
which object would be on the left and which would be on the right. Participants were
given breaks after every 7 minutes of testing.
Scoring
Participant responses were stored in 7 x 7 preference matrices (see Figure 4a).
This approach (patterned after Ledda et al., 2005) allows for easy analysis of the results.
Eight preference matrices were generated for each participant: four for the teapot data set
presented against each of the 4 possible backgrounds and likewise four for the color patch
data set. A preference matrix is best interpreted in a row-wise fashion. For example in
Figure 4a, the 1's in the first row specify that the purple teapot appears closer than the
orange and red teapots.
RESULTS
Corresponding preference matrices of all participants were summed together to
form eight cumulative preference matrices. Figure 4b shows the cumulative matrix for
the 15 participants for the teapot data set presented against the black background.
Summing across each row produces a score for each colored teapot (shown in last
column). This score tells how many times a given teapot was chosen as “nearer” relative
to all other teapots. Figure 5 shows plots of the scores for each teapot and color patch
against each of the 4 backgrounds. The two darker uniform backgrounds were darker than
the average luminance of the stimuli while the two lighter uniform backgrounds were
Depth by Color
9
lighter than the average luminance of the stimuli. Notice that when stimuli were
presented against the darker backgrounds that a clear cyclic trend emerged in the scores
from cool to warm. This cyclic behavior correlates nicely with the familiar circular
representation of the color spectrum.3 Notice however that as the background luminance
increased that this cyclic relationship was lost. This suggests that the relative strength of
color as a depth cue is enhanced against darker backgrounds.
Figure 6 shows plots of all the recorded response times as a function of variance
from the expected mean probability (0.5). The red line in each plot illustrates the best
linear fit of the data. Guibal and Dresp (2004) observed a correlation between the
probability of a “near” response and the associated response time (the higher the
probability, the shorter the response time) for simple highly saturated stimuli. Such
observations are often used to help validate experimental setup. We observed similar
trends in our experiment as illustrated in Figure 6.
Figure 7 and Figure 8 show the average probability of responding “near” for each
of the teapots and color patches over the 4 possible backgrounds. The trends in the
average probability of responding “near” for each color patch (Figure 7) revealed less
variability than the corresponding trends for the teapots (Figure 8). This is evidenced by
the relatively smooth functions for the color patches. Note that for the color patches, red,
which has been established in the literature as appearing nearer, does indeed show this
pattern: the red patch was chosen reliably more than the purple, cyan, green, yellow and
orange patches. In the teapots however, the red teapot was chosen reliably more than the
cyan, green, and yellow teapots only. Additionally, the warm orange color which
Depth by Color 10
received a high probability of being reported as “near” for the color patches was less
effective when applied to the teapot.
DISCUSSION
The present study was conducted to explore the effect of color on the perceived
depth of realistic objects. Previous studies using simple stimuli have been useful in
isolating and studying depth cues in certain contexts, but have left open the question of
whether the human visual system operates similarly for realistic objects. The results
presented here suggest that the more complex an image is, the more an observer may try
to gather multiple depth cues from that image, supporting the strong observer theory
(Doorschot, Kappers, & Koenderink, 2001; Guibal & Dresp, 2004; Landy et al., 1995).
When complex images are viewed, such as the teapots, color is not necessarily the
overriding depth cue. Additionally, the results show that there are circumstances under
which the relative strength of color as a depth cue can be enhanced. For both the simple
patches and the more complex teapots, color functioned as a more powerful depth cue
against darker backgrounds than against lighter backgrounds. These results provide
valuable insight into the impact of luminance contrast on our depth perception.
The observations made in this experiment have several useful applications to the
field of Computer Graphics. First, many modern software systems such as 3D-modeling
programs, paint programs, or even word processors and spreadsheets have a plethora of
user options available. This often leads to complex user interfaces with numerous
buttons, sliders, and drop-down menus in multiple panels. The clever use of nonperspective depth cues such as color may further enhance the readability and hence userfriendliness of such complex user-interfaces. By incorporating our observations during
Depth by Color 11
the user-interface design stage of the software development process, suitable colors can
be selected to ensure that these goals are met. Second, several recent studies have shown
that humans generally underestimate distance and depth4 in virtual environments (Loomis
& Knapp, 2003; Thompson, Willemsen, Gooch, Creem-Regehr, Loomis, & Beall, 2004;
Willemsen & Gooch, 2002). Our observations can be used to guide the selection of color
to help improve the perceived depth of objects displayed on such systems. Finally,
consider an electronic visual alert or warning system that demands quick attention. Our
results (in addition to that of Guibal and Dresp (2004)) show that certain foreground /
background color combinations result in stronger depth cues and that participants
responded quicker to these cues. By making informed color selection decisions, an
additional depth cue can be introduced which might bring the alert into awareness
quicker than an otherwise equal alert that did not capitalize on this cue.
Depth by Color 12
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Depth by Color 16
Footnote
1
Physicists use the opposite terminology: on a black-body radiator, bluer colors
are said to be hot while redder colors are said to be cool.
2
This particular teapot was chosen because it appeared natural regardless of its
3
The color spectrum is often presented as a continuous color wheel with red
color.
blending into purple. The original color wheel is credited to Sir Isaac Newton
(1704/1966).
4
The terms distance and depth are often incorrectly used interchangeably. In the
context of virtual environments, distance can either be defined to be egocentric (distance
from self) or exocentric (relative distance between objects). Depth refers to egocentric
distance.
Depth by Color 17
Figure Captions
Figure 1. (a) Response of the long, medium, and short wavelength (L, M, and S) sensitive
cones to different wavelengths of light. Data based on experiments conducted on human
observers (Stockman & Sharp, 2000; Stockman, Sharp, & Fach, 1999). (b) Chromatic
aberration. Assumes eye is red accommodated. Adapted from Sundet (1978).
Figure 2. (a) Original teapot photograph. Courtesy of Jack Tumblin and Ankit Mohan.
(b) Manually selected perceptually distinct colors. (c) Adjusted equiluminant colors.
Figure 3. Stimuli used in experiment: (a) teapots and (b) uniform color patches.
Figure 4. (a) Preference matrix. A 1 in row i, column j signifies that stimulus i appeared
closer than stimulus j. (b) Cumulative matrix for teapot data set against black
background.
Figure 5. (a) Cumulative scores for each teapot against each of the 4 backgrounds. (b)
Cumulative scores for each color patch against each of the 4 backgrounds.
Figure 6. (a) Participant response times for teapot data set against each of the 4
backgrounds as a function of variance from the expected mean probability (0.5). (b)
Participant response times for color patch data set against each of the 4 backgrounds as a
function of variance from the expected mean probability (0.5). The red line in each plot
illustrates the best linear fit of the data.
Figure 7. Average probability of responding “near” for each of the teapots over the 4
possible backgrounds.
Figure 8. Average probability of responding “near” for each of the color patches over the
4 possible backgrounds.
Depth by Color 18
Figure 1
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Figure 2
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Figure 3
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Figure 4
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Biographies
Reynold J. Bailey
Department of Computer Science and Engineering, Washington University in St. Louis
M.S. Computer Science, 2004, Washington University in St. Louis, USA
Cindy M. Grimm
Department of Computer Science and Engineering, Washington University in St. Louis
Ph.D. Computer Science, 1996, Brown University, Rhode Island, USA
Christopher C. Davoli
Department of Psychology, Washington University in St. Louis
B.S. Psychology, 2004, Davidson College, North Carolina, USA
Richard A. Abrams
Department of Psychology, Washington University in St. Louis
Ph.D. Psychology, 1986, University of Michigan, USA