Investigations into optimal color and shape primitives

Investigations into optimal color and shape primitives using the Perspecta 3D volumetric display George A. Reisa, Paul R. Haviga, Eric L. Hefta, John P. McIntireb a

Air Force Research Laboratory, AFRL/RHCV, Wright-Patterson Air Force Base, OH b General Dynamics Advanced Information Systems, Dayton, OH ABSTRACT

Volumetric displays allow users to view freely three-dimensional (3D) imagery without special eyewear. However, due to low display resolution, many colors appear distorted compared to their representation on a flat-panel display. In addition, due to the unique nature of the display, some shapes, objects, and orientations can also appear distorted. This study examines the perceptual range of virtual objects in a Perspecta 3D volumetric display to determine which combination of object type, size, position, and color produces the best perceived 3D image. Across three experiments, we test different object types, hues, saturation levels of hues, and position within the volumetric display. Participants rated their hue and shape naming confidence as well as their ratings on solidity. Various significant main and interaction effects were exhibited among three separate experiments. Keywords: hue, shape, saturation, size, perception, Perspecta, 3D, volumetric display

INTRODUCTION Three dimensional (3D) displays are emerging in gaming and entertainment, business, and command and control environments. For military command and control, 3D displays could be used to present virtual battlespaces as well as data structures or pictographic imagery. To fully understand the potential of 3D displays for military command and control (as well as other contexts), we need to understand the perceptual range given the imagery provided by 3D displays, the methods by which we measure 3D display parameters, and the methods of evaluation of 3D displays. Although the jump from cathode ray tubes (CRTs) to liquid crystal displays (LCDs) was indeed a major technological shift, at least two things remained the same─the viewer of the display observed a flat screen (relatively flat for CRT) and the focal point for the visual system remained the same. To add, many methods of measurement for certain parameters remained the same (e.g., measuring luminance output). The comparison of 3D displays with CRTs or LCDs is quite a different story. There are a number of technologies that provide 3D visualization (e.g., autostereoscopic, volumetric displays, computer-generated holography, and projector based concepts1). Each of these technologies provides imagery in a very disparate manner. For semantic purposes, we note that 3D visualization does not include that of 2.5D, also referred to as 3D perspective imagery on an LCD. To compare and evaluate these 3D technologies requires investigation into different evaluation metrics for 3D displays. Havig, Aleva, Reis, Moore, and McIntire (2007) discuss such metrics in terms of system metrics (input and output of the display), objective metrics (e.g., resolution, luminance output), subjective metrics (feelings, opinion, or attitude of the human observer), and objective-subjective metrics (human performance-based metrics)2. Each type of metric should be analyzed as each helps determine the utility of the display. In this study, we examine subjective metrics for Actuality Medical’s Perspecta 3D display3. This display generates a 10-inch diameter space that can present volume-filled imagery with a full 360-degree field of view. One hundred ninetyeight 2D slices are projected onto a rotating screen (900 rpm) enabled through a digital light processing projector. Each image is just one “slice” of the 3D image and each image has a 768 x 768 pixel resolution. True 3D imagery is perceived when the eyes see all the images together. Reis, Havig, Heft, McIntire, and Bell (2007) examined the perceptual range of virtual objects in the Perspecta 3D volumetric display to determine which combination of object type, size, and color produced the “best” 3D image4. Participants viewed combinations composed of three object types (vertical square plane, empty cube, filled cube) x three sizes (small, medium, large) x seven colors (red, green, blue, cyan, magenta, yellow, white). Participants in the study found that the color consistency was not uniform for different object types and color. Shape quality was observed as being different for different object types and sizes. Flicker was perceived as being different for object size and color. In addition, many interactions existed among the different variables across the dependent subjective variables. The point to

Display Technologies and Applications for Defense, Security, and Avionics II, edited by John Tudor Thomas, Andrew Malloy, Proc. of SPIE Vol. 6956, 69560C, (2008) · 0277-786X/08/$18 · doi: 10.1117/12.776764 Proc. of SPIE Vol. 6956 69560C-1 Downloaded from SPIE Digital Library on 05 Mar 2010 to 134.131.125.50. Terms of Use: http://spiedl.org/terms

be made is that designers of imagery must understand how primitives and basic colors are perceived before complex imagery is presented on the display. In this study, we continue exploring the basic elements that might be used for image creation. We performed three experiments that in unison provide a better understanding of how these elements are perceived. We ultimately want to provide information on how to build better imagery and evaluation methods for functionality.

2. EXPERIMENT 1 2.1 METHOD 2.1.1 Participants Ten participants (seven males, three females) were shown stimuli presented on the Perspecta. They ranged from 22 to 46 years of age and had normal or corrected to normal visual acuity as well as normal color vision and depth perception. 2.1.2 Stimuli In a light-proofed room, participants viewed different imagery on the Perspecta. Each image presented one of nine objects: • A cube with a point cloud fill for the inside of the cube and its faces filled in. • A cube with a point cloud fill for the inside of the cube and its faces not filled in. • A cube with a cascading fill for the inside of the cube and its faces filled in. • A cube with a cascading fill for the inside of the cube and its faces not filled in. • A cube with no fill and its faces filled in. • A cube with no fill inside and without its faces filled in (just a wire frame). • A square plane with a point cloud fill. • A square plane with a cascading fill. • A square plane with no fill (just a wire frame). The square planes contained an area of 1.45 inches^2 and the cubes contained a volume of 1.45 inches^3. All images were centered in the 10-inch diameter viewable space of the display. The point cloud fill consisted of 60,000 points chosen at random such that the position of each point fell inside the bounds of the cube. The cascading fill is achieved by drawing the base object 100 times scaled from 1% to 100%. For example, a cube that is 99% of the original base object is placed inside the base object. Then, a cube 98% of the base object is placed inside of the 99% cube⎯and so on. The wire frames were built with Open Graphics Library (Open GL) line primitives and when faces were filled on the cubes, the Open GL quad primitives were used. The Open GL line primitives were used to outline the squares and cubes on all images. The square planes were presented at one of three orientations: 0° (horizontal), 45°, and 90° (vertical). Each image was presented with one of seven hues: red, green, blue, cyan, magenta, yellow, and white. The hues were created by turning on, to the maximum output, different combinations of the primary color channels. For example, a red square was created with the red channel fully on and with the green and blue channels off. The hue of each image was presented in one of four saturation levels: Full saturation, 75% saturation, 50% saturation, and 25% saturation. Figure 1 shows a subset representation of the imagery.

Figure 1. A representation of the vertical square plane, a representation of the empty cube (wire framed), and a representation of the filled cube is shown from left to right, respectively.

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2.1.3 Procedure Participants were briefed on the experiment before they were tested. In each of the 420 trials, after observing the imagery, the participants were asked three questions: • What is the hue (choose from red, green, blue, cyan, magenta, yellow, and white)? • Rate your confidence that you correctly named the hue (1-5, 1 = not confident, 3 = somewhat confident, 5 = very confident). • Rate how solid the imagery appears (1-5, 1 = not solid, 3 = somewhat solid, 5 = very solid). Each participant received 20 practice trials chosen at random from the possible 420 experimental trials. From previous experience, we have observed that allowing for previous exposure of the imagery allows the participants to develop consistency throughout the testing as participants sometimes answer the questions based on previous trials. If this is the case, then the front-end trials are answered based on the practice trials. The 420 experimental trials were randomly presented to each participant.

2.2 RESULTS The data collected for the cubes were analyzed separately from the data collected for the square planes. The analysis for the cubes was conducted using a three-way completely within-subjects analysis of variance (ANOVA) and the analysis for the squares was conducted using a four-way completely within-subjects ANOVA. Due to the numerous significant effects in all three experiments, graphs of the effects were limited to those that encapsulated significant variables and were of interest. The analysis variables are listed below for each analysis in Experiment 1. Variables for Analysis with Cubes 6 Fills 7 Hues 4 Saturations

inner could fill / face filled, inner cloud fill / no face fill, inner cascading fill / faced filled, inner cascading fill / no face fill, no inner fill / faced filled, no inner fill / no face filled (wired framed) red, green, blue, cyan, magenta, yellow, white full saturation, 75% saturation, 50% saturation, 25% saturation

Variables for Analysis with Squares 3 Fills 3 Angles 7 Hues 4 Saturations

cloud fill, cascading fill, no fill (wire framed) 0° (horizontal), 45°, 90° (vertical) red, green, blue, cyan, magenta, yellow, white full saturation, 75% saturation, 50% saturation, 25% saturation

2.2.1 Hue naming for cubes and squares There was 2.7% error in hue naming across cubes and squares. Of that 2.7%, the predominant hues confused were between cyan and white and to a lesser degree between magenta and red and between yellow and green. 2.2.2 Hue confidence for cubes With the hue confidence rating as the dependent variable (DV), all main and interaction effects were significant except for the Fill x Hue interaction. The rank-ordered means for the main effects are listed in Table 1. Figure 2 shows the means for the confidence ratings in the Fill x Hue x Saturation interaction. TABLE 1. Means for Hue Confidence for Cubes. Fill Cascade Fill / No Face Fill Cloud Fill / No Face Fill Cloud Fill / Face Fill Cascade Fill / Face Fill No Fill / Face Fill No Fill / No Face Fill

Mean 4.83 4.81 4.80 4.78 4.75 4.28

Hue blue magenta red green white yellow cyan

Mean 4.87 4.85 4.80 4.80 4.73 4.55 4.33

Saturation 75% 100% 50% 25%

Mean 4.81 4.79 4.76 4.49


Cloud Fill / No Face Fill 5

4.5

4.5

Confidence Rating

Confidence Rating

Cloud Fill / Face Fill 5

4

3.5

3

3.5

3

25 50 75 100

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25 50 75 100

2.5

25 50 75 100

2.5

4

red

green

blue

cyan

magenta

yellow

white

red

green

blue

cyan

magenta

yellow

white

Saturation X Hue

Saturation X Hue

Cascade Fill / No Face Fill 5

4.5

4.5

Confidence Rating

Confidence Rating

Cascade Fill / Face Fill 5

4

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3

2.5

4

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3

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red

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cyan

magenta

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cyan

magenta

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white

Saturation X Hue

Saturation X Hue

No Fill / No Face Fill 5

4.5

4.5

Confidence Rating

Confidence Rating

No Fill / Face Fill 5

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4 3.5 3 2.5

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red

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Saturation X Hue

Saturation X Hue

Figure 2. The means for confidence ratings are shown for the significant Fill x Hue x Saturation interaction. In the chart titles, Cloud Fill = Inside of cube was filled with point cloud algorithm, Cascade Fill = The inside of the cube was filled with the cascading algorithm, No Fill = The inside of the cube was not filled, Face Fill = The faces of the cubes were filled, No Face Fill = The faces of the cubes were not filled. Note: ordinate scale ranges from 2.5 – 5.

2.2.3 Solidity rating for cubes With the solidity rating as the DV, all main and interaction effects were significant except for the Fill x Hue interaction. The means for the main effects are listed in Table 2.


TABLE 2. Means for Solidity Ratings for Cubes Fill Cloud Fill / Face Fill Cascade Fill / Face Fill Cloud Fill / No Face Fill Cascade Fill / No Face Fill No Fill / Face Fill No Fill / No Face Fill

Mean 3.28 3.27 3.08 2.77 2.46 2.40

Hue magenta green yellow white cyan red blue

Mean 2.97 2.96 2.94 2.90 2.80 2.79 2.76

Saturation 100% 75% 50% 25%

Mean 3.12 3.09 2.90 2.33

2.2.4 Hue confidence for squares With the hue confidence rating as the DV, all main and most interaction effects were significant. The means for the main effects are listed in Table 3. For this analysis we chose to show two of the two-way interactions in Figure 3.

TABLE 3. Means for Hue Confidence for Squares Mean 4.74 4.71 4.27

Hue blue magenta red green white yellow cyan

Mean 4.80 4.78 4.74 4.65 4.47 4.36 4.19

Saturation 100% 75% 50% 25%

5.00

5.00

4.75

4.75

Confidence Rating

4.50 4.25 4.00 3.75

Mean 4.79 4.77 4.59 4.14

Angle 90 deg 45 deg 0 deg

Mean 4.68 4.57 4.48

4.50 4.25 4.00 3.75 3.50

3.50

90

Cascade Fill

0

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90

No Fill - Wire Framed

25 50 75 100

45

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Could Cloud FillFill

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Confidence Rating

Fill Cascade Fill Cloud Fill No Fill

cyan

blue

green

magenta

red

white

yellow

Angle X Fill

Hue X Saturation

Figure 3. The means for hue confidence ratings for squares are shown for the significant Angle x Fill and Hue x Saturation interactions. Note: ordinate scale ranges from 3.25 – 5.00. 2.2.5 Solidity rating for squares With the solidity rating as the DV, all main effects, most two-way and some higher order interactions were significant. The means for the main effects are listed in Table 4. For this analysis we chose to show two of the two-way interactions in Figure 4.


TABLE 4. Means for Solidity Ratings for Squares Mean 3.05 2.76 2.33

Hue green magenta yellow white red cyan blue

Mean 2.80 2.77 2.76 2.71 2.69 2.66 2.62

Saturation 100% 75% 50% 25%

4.00

4.00

3.50

3.50

3.00

3.00

Solidity Rating

2.50

2.00 1.50

Mean 3.28 3.08 2.71 1.79


Mean 3.20 2.64 2.30

2.50

2.00

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1.00

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45 90

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0

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45 90

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Cloud Fill

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1.00 0

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Solidity Rating

Fill Cascade Fill Cloud Fill No Fill

cyan

blue

green

magenta

red

white

yellow

No Fill - Wireframe

Hue X Saturation

Fill X Angle

Figure 4. The means for solidity ratings are shown for the significant Fill x Hue and Hue x Saturation interactions. Note: ordinate scale ranges from 1.00 – 4.00.

3. EXPERIMENT 2 3.1 METHOD In Experiment two, we explored the perceptual differences that may occur between observing imagery in the middle of the display as compared to off-center. 3.1.1 Participants The participants were the same as in Experiment 1. 3.1.2 Stimuli The stimuli in Experiment 2 were the same as in Experiment 1 with the addition that in each trial the same image was presented to the left and to the right sides of the image. Two adjacent images were 2.18 inches from center to center in the X axis. 3.1.3 Procedure Participants were briefed on the experiment before they were tested. After observing the imagery in each trial, the participants were asked five questions: • What is the hue, overall, of the images (choose from red, green, blue, cyan, magenta, yellow, and white)? • Rate your confidence that you correctly named the hue (1-5, 1 = not confident, 3 = somewhat confident, 5 = very confident). • Rate the similarity in hue between the center and side items (1-5, 1 = not similar, 3 = somewhat similar, 5 = very similar).


• Rate how solid the center imagery appears (1-5, 1 = not solid, 3 = somewhat solid, 5 = very solid). • Rate how solid the side imagery appears (1-5, 1 = not solid, 3 = somewhat solid, 5 = very solid). Before beginning data collection, participants received 20 practice trials chosen at random from the possible 420 experimental trials.

3.2 RESULTS The independent variables for cubes and squares were the same as in Experiment 1. The DVs were hue naming and hue naming confidence, hue similarity rating (between center and side items), solidity rating of center items, and solidity rating of side items. Results were analyzed using a four-way completely within-subjects ANOVA. 3.2.1 Hue naming for cubes and squares There was 2.3% error in color naming across cubes and squares. Of that 2.3%, the predominant colors confused were between cyan and white and to a lesser degree between magenta and red and between yellow and green⎯same as in Experiment 1. 3.2.2 Hue confidence for cubes With the hue confidence rating as the DV, all main and interaction effects were significant except for the three-way interaction. The means for the main effects are listed in Table 5. For this analysis we chose to show two of the two-way interactions in Figure 5.

5.00

5.00

4.75

4.75

4.50

Confidence Rating

Confidence Rating

TABLE 5. Means for Hue Confidence for Cubes Fill Mean Hue Cascade Fill / No Face Fill 4.83 red Cascade Fill / Face Fill 4.82 blue Cloud Fill / Face Fill 4.80 magenta Cloud Fill / No Face Fill 4.79 green No Fill / No Face Fill 4.73 white No Fill / Face Fill 4.36 yellow cyan

4.25 4.00 3.75

Mean 4.83 4.83 4.80 4.77 4.71 4.59 4.48

Saturation 100% 75% 50% 25%

Mean 4.80 4.79 4.78 4.52

4.50 4.25 4.00 3.75

3.50 3.50

25 50 75 100

25 50 75 100

25 50 75 100

25 50 75 100

3.25 25 50 75 100

No Fill / No Face Fill

25 50 75 100

Cloud Fill / Cascade No Face Fill Fill / No Face Fill

25 50 75 100

No Fill / Face Fill

25 50 75 100

25 50 75 100

Cascade Fill / Face Fill

25 50 75 100

25 50 75 100

Cloud Fill / Face Fill

25 50 75 100

25 50 75 100

3.25

cyan

blue

green

magenta

red

white

yellow

Fill X Saturation

Hue X Saturation

Figure 5. The means for hue confidence are shown for the significant Fill x Saturation and Hue x Saturation interactions. Note: ordinate scale ranges from 3.25– 5.00.


3.2.3 Hue similarity between side and center for cubes For hue similarity, the only significant effects were contained within Saturation, Fill x Saturation, and Fill x Saturation X Hue. The means for the main effects are listed in Table 6. TABLE 6. Means for Hue Similarity Between the Center and Side Cubes. Fill Cascade Fill / No Face Fill No Fill / No Face Fill Cloud Fill / Face Fill Cascade Fill / Face Fill Cloud Fill / No Face Fill No Fill / Face Fill

Mean 4.52 4.51 4.29 4.28 4.22 4.17

Hue green yellow white magenta blue red cyan

Mean 4.38 4.37 4.34 4.34 4.31 4.30 4.27

Saturation 100% 75% 50% 25%

Mean 4.45 4.41 4.35 4.11

3.2.4 Solidity of center item for cubes For solidity ratings of the center item, the only significant effects were contained within Saturation, Fill, Fill x Saturation, and Fill x Hue. The means for the main effects are listed in Table 7. TABLE 7. Means for Solidity Ratings for Center Cubes. Fill Cascade Fill / Face Fill Cloud Fill / Face Fill Cloud Fill / No Face Fill Cascade Fill / No Face Fill No Fill / No Face Fill No Fill / Face Fill

Mean 3.52 3.48 3.35 3.17 2.71 2.58

Hue cyan green white yellow magenta red blue

Mean 3.19 3.19 3.17 3.15 3.12 3.11 3.03

Saturation 100% 75% 50% 25%

Mean 3.36 3.24 3.18 2.76

3.2.5 Solidity of side item for cubes For solidity ratings of the side items, all effects were significant except for the three-way interaction. The means for the main effects are listed in Table 8. TABLE 8. Means for Solidity Ratings for Off-center Cubes. Fill Cloud Fill / Face Fill Cloud Fill / No Face Fill Cascade Fill / Face Fill Cascade Fill / No Face Fill No Fill / No Face Fill No Fill / Face Fill

Mean 3.57 3.29 3.27 3.22 2.71 2.39

Hue white green yellow cyan magenta red blue

Mean 3.18 3.16 3.14 3.13 3.07 2.98 2.86

Saturation 100% 75% 50% 25%

Mean 3.45 3.31 3.14 2.39

3.2.6 Hue confidence for squares With the hue confidence rating as the DV, all main effects, most two-interactions, and a couple of higher order interaction effects were significant. The means for the main effects are listed in Table 9. TABLE 9. Means for Hue Confidence for Squares Fill Cascade Fill Cloud Fill No Fill

Mean 4.73 4.73 4.35

Hue magenta blue red green white cyan yellow

Mean 4.78 4.77 4.76 4.70 4.52 4.34 4.34

Saturation 100% 75% 50% 25%

Mean 4.79 4.76 4.65 4.20



Mean 4.68 4.58 4.55

3.2.7 Hue similarity between side and center for squares With the hue similarity rating as the DV, angle, hue, and saturation effects were significant. Most two-way interactions and a couple of higher order interactions were also significant. The means for the main effects are listed in Table 10. TABLE 10. Means for Hue Similarity Ratings for Squares Fill No Fill Cloud Fill Cascade Fill

Mean 4.02 3.80 3.79

Hue green cyan yellow white magenta blue red

Mean 4.06 3.89 3.89 3.87 3.83 3.78 3.72

Saturation 100% 75% 50% 25%

Mean 4.09 4.01 3.83 3.52


Mean 4.18 4.04 3.38

3.2.8 Solidity of center item for squares With solidity ratings of the center items as the DV, all main effects, most two-way interactions, and one three-way interaction was significant. The means for the main effects are listed in Table 11. TABLE 11. Means for Solidity Ratings of Center Items for Squares Fill Cascade Fill Cloud Fill No Fill

Mean 3.38 3.22 2.60

Hue yellow green cyan magenta white red blue

Mean 3.17 3.14 3.12 3.12 3.06 3.01 2.87

Saturation 100% 75% 50% 25%

Mean 3.50 3.38 3.08 2.32


Mean 3.45 3.00 2.76

3.2.9 Solidity of side item for squares With solidity ratings of the side items as the DV, all main effects, some two-way interactions, and one higher order interaction was significant. The means for the main effects are listed in Table 12. TABLE 12. Means for Solidity Ratings of Side Items for Squares Fill Cascade Fill Cloud Fill No Fill

Mean 2.95 2.79 2.28

Hue green cyan yellow magenta white red blue

Mean 2.76 2.76 2.74 2.69 2.69 2.55 2.50

Saturation 100% 75% 50% 25%

Mean 3.35 3.04 2.58 1.72


Mean 2.99 2.55 2.47

4. EXPERIMENT 3 4.1 METHOD 4.1.1 Participants The participants were the same as in Experiments 1 and 2. 4.1.2 Stimuli Participants viewed imagery in the Perspecta display. They were tested on 240 trials. The objects in the imagery took on one of four shapes: pyramid, cube, sphere, or diamond. Each shape was displayed at one of 10 sizes. First, we note the volumes of the base shapes from which the sizes were determined. They were:


• Cubes were 1.45 inches x 1.45 inches x 1.45 inches and had a volume = 3.08 inch^3 • Spheres were 1.80 inches in diameter and had a volume = 3.07 inch^3 • Pyramids were 1.91 inches high with a base 2.20 inches wide, volume = 3.08 inch^3 • Diamonds were 2.32 inches high with a base 2.00 inches wide, volume = 3.08 inch^3 All objects in Experiment 3 are scaled down to 1.0%, 1.5%, 2.0%, 2.5%, 3.0%, 3.5%, 4.0%, 4.5%, 5.0%, and 10% of their volume in the base shapes. At each of the objects and size level, the imagery was displayed with one of the three fills as described in Experiment 1: cloud fill, cascading fill, no fill (wire framed). The imagery was presented either centered in the display or off to the side. The faces of the shapes were not filled. 4.1.3 Procedure Participants were briefed on the experiment before they were tested. After observing the imagery in each of the 240 trials, the participants were asked three questions: • What is the shape (choose from pyramid, cube, sphere, diamond)? • Rate your confidence that you correctly named the shape (1-5, 1 = not confident, 3 = somewhat confident, 5 = very confident). • Rate how solid the imagery appears (1-5, 1 = not solid, 3 = somewhat solid, 5 = very solid). • Each participant received 20 practice trials chosen at random from the possible 240 experimental trials. The 240 experimental trials were randomly presented to each participant.

4.2 RESULTS Results were analyzed using a four-way completely within-subjects ANOVA. Data were analyzed for only the shapes that were named correctly. 4.2.1 Shape naming There was a 15% error rate in naming the shapes. The main contributor to this error was the scale variable. Shapes presented at sizes 2.5% or less were most likely to be named wrong. The most confusable shapes were between spheres and cubes, and the second most confusable shapes were between spheres and diamonds. Figure 6 shows a graph of the error rates for the different shapes across the different levels of scale. 70.0 Cube Diamond

60.0

Pyramid Sphere

Error Rate (%)

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Figure 6. The mean error rates are shown for shape naming across the levels of scale for the four different shapes.


4.2.2 Shape Confidence With shape confidence as the DV, all main effects, two-way interactions effects, and most three-way interactions effects were significant. The means for the main effects are listed in Table 13. TABLE 13. Means for Shape Naming Confidence. Shape

Means

Fill

Means

Position

Means

Scale

Means

pyramid

4.37

cloud

4.11

center

4.17

10.0%

4.93

diamond cube sphere

4.13 3.86 3.78

no fill cascade

4.03 3.99

side

3.90

5.0% 4.5% 4.0% 3.5% 3.0% 2.5% 2.0% 1.5% 1.0%

4.69 4.57 4.43 4.35 4.04 3.75 3.24 2.66 1.77

4.2.3 Shape Solidity With the shape solidity rating as the DV, all main effects, most two-way interaction effects, and all three-way interactions effects were significant. The means for the main effects are listed in Table 14. TABLE 14. Means for Shape Solidity Rating. Shape

Means

sphere

3.76

cloud

Fill

Means 3.74

center

Position

Means 2.22

Scale 10.0%

Means 3.61

diamond pyramid cube

3.30 3.21 3.13

cascade no fill

3.46 2.80

side

1.90

2.0% 1.5% 5.0% 4.5% 2.5% 3.5% 4.0% 3.0% 1.0%

3.37 3.36 3.36 3.34 3.29 3.27 3.26 3.24 3.18

4. DISCUSSION AND CONCLUSIONS ACROSS THE THREE EXPERIMENTS The experiments in this paper attempted to add knowledge regarding perception of color and shape primitives in imagery presented in the Perspecta volumetric display. The variables we chose in our study are ones that we think designers may contend with when creating imagery for volumetric displays. For example, designers might want to consider what hues are best perceived, and for what construct⎯having a sense that the imagery is solid or having confidence that the human actually perceives the hue the designer wants the human to perceive. We also considered saturation. When would a designer want to desaturate part of the imagery and what does that do to perception? We considered fill algorithms. Some algorithms may provide a better sense of an object’s solidity. These fills may reflect upon the update frame rate of the imagery. Designers might want to consider form versus function in their filling algorithms. We explored angular positioning of square planes and positioning of imagery in the XY space of the display (center vs. off-center). Much was explored in this study and clearly a myriad of other factors and levels can be analyzed. There was a multitude of results obtained from the study. After considering the amount of data that was produced, it was unfeasible to graph all means and present all ANOVA tables. Readers are invited to contact the authors for details of the study. There were a host of interactions but only main effect means were presented. Just the multitude of interactions


across the three experiments reveals that designers must understand the relationships that variables have on each other. For example, confidence in hue naming may depend on certain hues at some saturation levels and other hues on other saturation levels. In general, highly saturation hues tended to produce higher ratings. As mentioned earlier, there were many interactions. For the sake of practicality, here we will discuss mostly main effects in general terms. A glance over the tabled means across the experiments reveals some interesting trends. For confidence in hue and shape naming, as well as solidity rating, having a filled volume is better than just showing its frame. In addition, although not always the case, the cascading fill tended to produce higher ratings. Regarding hue, designers should consider trade-offs between hue confidence and solidity rating. For example, blue, in general, appears at the top of the lists for hue confidence but at the bottom of the lists for solidity rating. In Experiment 2, although not tested in formal analysis, solidity ratings of center square planes were higher than scores off-center, but this did not hold for cubes. The center imagery’s higher ratings hold for shape naming in Experiment 3 where position was tested and was found to be significant. Shapes presented in the center of the display were found to be more solid (perceptually). Another interesting point from Experiment 3 was the matched rank ordering of scale values with confidence. This does not hold for solidity⎯possibly because as items become smaller there is less emptiness in the shape and is perceived and being denser. From this study, it is apparent that many factors influence our perception in the Perspecta volumetric display. There are trade-offs that need to be considered when creating the imagery, and function versus form should also be considered. This leads into the payoffs of future development of such a technology. For command and control decision makers to utilize such a display, the evolution of the mechanisms that drive these volumetric displays will need to take place. Three-dimensional displays will have their place in many contexts. It is not only through hardware development that will feed the evolution, but research in objective, subjective, and performance-based studies as well. Our intent was to add knowledge to our previous study so that the continuing design of the mechanisms that drive volumetric displays and the imagery, created through software, is enhanced. Continuing evolution of volumetric displays may one day allow command and control decision makers to utilize such a technology for battlespace visualization or data exploration.

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