6.4.1 Introduction
We have previously tried several different iterations of the experiment, attempting to find a way to successfully cause a luminance segregation cue to be associated with the disparity cue. In the previous experiment, we have tried changing the luminance of the background to create a luminance edge near where disparity segregation occurs. Unfortunately, this has consistently created a percept of a shaded shape that is unrelated to the disparity defined object which we call the curtain effect. However, other changes such as the use of a black background and white dots helped stabilise the percept of the object. Here, we attempt to fuse the luminance edge with the disparity defined object by changing the luminance of the dots that make up the disparity defined object. This
should clearly associate the luminance as a property of the disparity defined object, potentially allowing the
luminance edge to interfere with the disparity segregation processes.
Although in Section 6.2 we found that adding the luminance cue to the dots caused the experiment to be very hard to complete, we have many improvements that should help:
1. We are using a black background (<0.01cd/m2) with mid-grey (18.67cd/m2, Michelson contrast 0.5) and white dots (37.09cd/m2, Michelson contrast 1), which should ensure both object and background dots visible.
2. Originally in Experiment 4 (Section 6.2), only half of the window dots (either the white or black dots) had a different luminance to the background dots. In this experiment, all the dots within the window will be white and all the dots outside will be mid- grey, making the luminance window better defined, with no dots in the window having the same luminance as dots present in the
background.
3. We are going to reduce the sizes of the luminance windows to the minimum possible that still creates a sufficient predicted difference to be experimentally detectable – this could further increase the relevance of the luminance cue to segregation. 4. Rather than applying the luminance increase over a set square area, we are going to
display dots as white if they are above a certain disparity and black if below. This
Figure 6.12: Anaglyph of stimuli in Experiment 6. Sharp object (top) and smooth (bottom), with a 1.125 fractional luminance window on the lower object
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means that the shape of the luminance window will correspond fully to the shape of the smooth object. We discuss this below.
We choose a horizontal distance from the centre of the window, and calculate the disparity of the smooth object at this point. We then draw a line of constant disparity, which follows the curved shape shown in Figure 6.13. We use this shape as our luminance window, which means that the shape of the luminance window now matches the shape of the smooth object.
6.4.2 Stimuli and methods
We return to the previous square shaped sharp and smooth objects. However, we keep the black background and white dots from the previous circular experiment as this appeared to increase the visibility of the object and the luminance window. The central region of dots inside the luminance window is white (37.09cd/m2, Michelson contrast 1), while the dots outside of the window are mid-grey (18.67cd/m2, Michelson contrast 0.5) on a black background (<0.01cd/m2) as shown in Figure 6.12. Dots outside the window are still easily visible, but the difference of dot luminance of 18.42 cd/m2 across the should make it clear that the luminance window is part of the disparity defined object, not a second object that is hanging behind a transparent disparity defined curtain. Additionally, the sharp object had the same increase in luminance that coincided with the disparity edge (square, side length of 171.1arcmin) to reinforce the luminance window as a cue to object segregation.
Smooth objects are displayed at smoothness coefficients of 3, 14 and 26 with seven
different peak depths as in Experiments 1 and 2, and compared directly to a sharp object of constant disparity. The luminance cue on the sharp object always corresponded to the disparity edge (171.2 arcmin), while the luminance cue on the smooth object was either 150.2, 171.2 (the same as the plateau size) or 193.2 arcmin across (fractional plateau size 0.875, 1 and 1.125).
Figure 6.13: Difference between the square luminance window in Experiment 4 (dotted line, Section 6.2) and the constant disparity defined luminance window used here (solid
line) Line of constant disparity Line of constant x
123 We ran the different luminance window
sizes through the model developed in Chapter 5 to obtain the predicted perceived peak depth for the objects with every combination of luminance windows size and smoothness coefficient. The model was run as if the luminance window dictated the area of the disparity defied object that was segregated and then averaged – this is the maximum effect that the luminance window could have on the perceived peak depth. These predictions are plotted in Figure 6.14.
The experimental setup was the same as in Section 3.1 and experimental procedure was the same as in Section 4.2.2. Participants were tasked to press either the up or down arrow buttons to indicate which object had a greater peak depth. Participants completed seven blocks of approximately 300 trials each, each of which took 10-15min to complete with a forced 60s break between the blocks. These blocks were completed in two sessions: In the first hour long session, participants completed the TNO test, then a demo, participants that could not complete these successfully (see Section 4.2.2) were rejected from further study. Participants then completed three blocks. In the second session Participants completed the remaining four blocks.
6.4.3 Results
Psychometric functions were fitted and the PSEs were extracted for each combination of smoothness coefficient and window size for each participant. We appear to have made the experiment much simpler to complete, with only one participant unable to complete the demo and two having PSEs outside of the extractable range, leaving five out of eight participants completing with usable data.
Each results graph in Figure 6.15 plots PSE against luminance window size for an object of a single smoothness coefficient. By comparing between the three graphs, we can see that the PSEs are greater in Figure 6.15c (SC14) than Figure 6.15a (SC3) and b (SC0), and greater in Figure 6.15b (SC3) than Figure 6.15a (SC0). Effectively, objects of greater smoothness coefficient have a greater PSE. This replicates the data in Chapters 4 and 5, where an increase in smoothness coefficient results in a decrease in the perceived peak depth of the object.
Looking at the change of window size with PSE within each of the three graphs in Figure 6.15 there appears to be no relation between the model-predicted PSEs (dotted line) and the observed data. Statistical analysis shows that there is no significant effect of window size on observed PSE at any smoothness coefficient (two way repeated measures ANOVA for
Figure 6.14: Predicted perceived peak depth for objects with each smoothness coefficient
with the size of the luminance window
5.5 6 6.5 7 7.5 8 8.5 140 160 180 200 P redi cte d P SE (arcm in )
Window Size (arcmin) SC 6
SC 14 SC 23
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window size, F(1.094,4.374) = 0.501, p=0.531 for window size and smoothness,
F(1.139,4.555) = 0.501, p=0.534 with a Greenhouse-Geisser correction for invalidation of the assumption of sphericity p<0.05).
(a) (b)
(c)
Figure 6.15: Predictions alongside participant performance with smoothness coefficients (a) 26 (b) 14 (c) 6.
6.4.4 Discussion
We successfully made the experiment simple enough that participants were able to
complete it without too much difficulty, although the error bars and dropout rates (2 out of 7 have extractable PSEs) are still a little large in comparison to the experiments in Chapters 4 and 5. However, the surprising result is that there is no effect at all of the luminance window size on the perceived disparity. This indicates that the luminance window is not affecting the area over which disparity segregation is taking place.
As the disparity is very well defined, even the smooth edge may provide a strong cue to object segregation. The luminance cues we have presented may be comparatively poor cue to the object’s edge as the luminance was delivered only via the positions of the random dots. As these dots are randomly placed, the edge of the luminance window appears uneven rather than a distinctive straight line, potentially weakening the strength of this cue to segregation. This may mean that the visual system is using the disparity cue to segregate the object and ignoring the more unreliable information provided by the luminance
window. 5 5.5 6 6.5 7 7.5 8 8.5 140 160 180 200 P SE (arcm in)
Window Size (arc min)
Par I Par J Par K Par L Par M Prediction 5 5.5 6 6.5 7 7.5 8 8.5 140 160 180 200 P SE (arcm in )
Window Size (arc min)
5 5.5 6 6.5 7 7.5 8 8.5 140 160 180 200 P SE (ar cm in )
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A similar problem was encountered by Lovell et al (2012) when investigating the
combination of shape from shading and shape from disparity – they found that the disparity cue could be strong enough that the shape from shading cue was ignored. We will therefore try the next step that they took in alleviating this problem – adding random noise to the disparity cue to make the disparity unreliable and harder to judge (Harris & Parker, 1992), thus forcing the visual system to rely more on the presence of the luminance cue for segregation.