The Effect of Object Color on Depth Ordering

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Report Number: WUCSE-2007-18

2007

The Effect of Object Color on Depth Ordering

Reynold Bailey, Cindy Grimm, Christopher Davoli, and Richard Abrams

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Recommended Citation 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. https://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. This technical report is available at Washington University Open Scholarship: https://openscholarship.wustl.edu/ cse_research/122 The Effect of Object Color on Depth Ordering

Reynold Bailey, Cindy Grimm, Christopher Davoli, and Richard Abrams

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. 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: [email protected]

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. ABRAMS 2

1Washington University in St. Louis, Department of Computer Science and Engineering,

St. Louis, Missouri, USA

2Washington 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: [email protected] Depth by Color 2

Abstract

Objective: 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.

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 color s 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 19 th 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 Depth by Color 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 three- dimensional 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 teapot 2 (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 within-

object 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 non- perspective depth cues such as color may further enhance the readability and hence user- friendliness 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 depth 4 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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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

color.

3 The color spectrum is often presented as a continuous color wheel with red

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 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