User Study 1.2: Local shape task

Subjects:Seven undergraduate and graduate students performed the local shape task. None of the seven took part in User Study 1.1. All had normal or corrected-to-normal vision and reported normal color sensitivity but were not tested. Participants were compensated for their time.

Stimuli:The participants viewed images of the bump data under the following visualization tech- niques: color mapping, principal curvature texture, and principal curvature texture with shadows.

Design: This user study compares the three visualization techniques for enabling the distance task. Each participant viewed 180 trials, as in User Study 1.1.

Participants estimated the local shape of each surface within indicated pairs of regions and re- ported which of the pair of regions contained the smallest orientation difference (the smaller angle difference between surface normals). The regions were selected such that the orientation differences for the intersecting surfaces within each region ranged from 0 to 70 degrees. The region pairs were selected such that the differences of orientation differences between two regions were uniformly dis- tributed between 0 and 45 degrees at 5 degree steps. The region locations were otherwise determined as in User Study 1.1. Trials were randomly ordered for each participant.

Participants were asked to respond to the following question:

In which circled region do the two surfaces appear to be more similarly oriented or parallel? Subjects received training as in Experiment 1.

Hypothesis

The hypothesis is that the percentage of correct participant responses depends on the visualization technique and on the difference between the region orientation differences.

Independent variables: The design directly manipulates two independent variables – the differ- ence between region orientation differences and the visualization technique. Also recorded are the following predictor variables: a random unique identifier for each participant, the participant’s gen- der, and the participant’s response time.

Dependent variable: The dependent variable in this experiment is the percentage of correct re- sponses.

I expected the percentage of correct participant responses to depend on the difference between the two region orientation differences and on the visualization technique. I expected that participants would be able to compare orientation differences in the color mapping technique by comparing color gradients in the marked regions. Because the distance between the two surfaces changes where the two surfaces have different orientations, the color changes there also. I expected cast shadows to enhance the perception of shape, especially on the interior surface. Finally, I expected the principal curvature techniques to enable better performance than the color mapping technique because they present geometry of both surfaces.

Results

Unless otherwise noted, independent variables have no statistical significance (p> .05).

Analysis:ANOVA analysis finds significant main effects for orientation difference between marked regions (p< .001), the visualization technique (p< .01), the participant (p< .01) and participant response time (p< .01). As the orientation difference increases, participants give more correct re- sponses. In fact, at a orientation difference of 0 participant responses are at chance, and the responses eventually plateau (larger differences in distances no longer produce an increased number of correct responses). Longer response times correlated to higher percentages of correct responses; this effect

User Study 1.2: Local Shape Task

Color Mapping Curvature Curvature + Shadows Display Technique

Correct (%)

Figure 5.7: This figure shows the overall percentages of correct responses and their 95% confidence intervals for the local shape task. Tukey’s HSD test finds that the two principal curvature texture techniques are statistically different from the color mapping technique, but not from each other.

could be from participants rocking the surface to understand the shape, but no count of the number of times participants’ rocked the surface was recorded so it can not be tested.

Figure 5.7 shows the overall percentages of correct responses and 95% confidence intervals by vi- sualization technique; the figure also shows that the performance of participants is better than chance. A Tukey’s HSD test finds that the two principal curvature texture techniques are better than direct color mapping but are not separable from each other.

Responses to the questionnaire show that the average participant found the principal curvature texture with shadows marginally clearer than color and either clearer than curvature texture alone. No preference was reported between color or curvature with shadows, but either was preferred over

curvature alone. As in the distance task, participants’ judgment of the ranking of the techniques does not match the study findings. Also, the results did not show the expected improvement in perception due to cast shadows for the two curvature techniques.

Discussion: The user study results show the principal curvature texture techniques enabled more correct responses to the local shape task than directly mapping distance to color. Principal curvature texture clearly enables better performance for the local shape task.

Again, the questionnaires show that subjective preference does not reflect objective performance. Participants expressed a preference for color mapping or principal curvature texture with shadows over curvature texture without shadows for the local shape tasks. This preferences can be supported by the performance results. In particular, it is interesting that participants preferred direct encoding of the metric to be estimated over a technique which enabled better task performance.

Again, shadows showed no benefit.