The perceived depth of plaids, measured by depth matches and by depth-interval matches, is a univariate function of disparity magnitude. Under the conditions of our experiments, perceived depth depends on disparity magnitude in the horizontal direction. The vertical components of the plaids' disparities, provided they are within tolerated limits, appear to make no contribution to perceived depth whether they are identical across the two stimuli or not. Thus, differences in the disparity directions do not enter into the calculation of the relative stereo depth of our 2-D stimuli.
A vast literature supports the dependence of stereo depth on horizontal disparity. Curiously, though, it has never before been tested as we have tested it here. The reason for this surely is that no need was seen for such a test. However, a stereo depth calculation that does not make use of horizontal disparities has been recently identified. The perceived depth of a grating relative to a plaid depends instead on the magnitude and direction of the disparity of one stimulus relative to those of the other (Chai & Farell,
2009; Farell et al.,
2009). This result seems a radical exception to the usual role of horizontal disparity in stereoscopic vision, but there is a region of overlap between the two depth calculations. Horizontal disparity does not predict depth match between a grating and a plaid in the general case. However, in two special—and important—cases, the depth matches predicted by disparity projection and by horizontal disparity are the same. One case occurs when the disparity direction of one or both of the stimuli is horizontal, and the other occurs when the disparity magnitude of the reference stimulus is zero (Farell et al.,
2009).
Of the many studies consistent with horizontal disparity as the metric on which stereo depth is calculated, the bulk falls into one or the other (and most often, both) of these special cases. These studies are also consistent with the projected disparity hypothesis. In the present experiments horizontal disparities and projected disparities predict different outcomes, which accounts for the uncertainty about how the data would turn out.
The outcome of our experiments here differs from what we have observed previously using grating-plaid pairs, yet the two results are compatible, not contradictory. The surprising lack of a contribution of horizontal disparity in the previous studies (Chai & Farell,
2009; Farell et al.,
2009) might indicate either of two things. It might be that horizontal disparity is not used to calculate the depth of 1-D stimuli or that horizontal disparity is not used to calculate the depth of stimuli whose disparities are non-horizontal. In fact, projected disparity predicts the depth of 1-D stimuli only; the present results show that the perceived depth of 2-D stimuli depends on horizontal disparities regardless of the stimulus disparity directions.
Perceived depth in our experiments depended on horizontal disparity over the full range (±60° of horizontal) of the disparity directions tested. This outcome held in the absence of a stimulus with a strictly horizontal or zero-magnitude disparity to act as a reference in the relative disparity computation. It held for depth matches, at which the perceived depth separation between the stimuli is zero, and it held for depth-interval matches, at which the same perceived depth separation exists across two stimulus pairs.
The difference in the depth calculations for 1-D and 2-D stimuli prompts an observation and a question. The observation is that this difference can lead to intransitive depth matches: A plaid might have the same perceived depth as a grating that in turn has the same perceived depth as another plaid, but in general these two plaids will not match in depth. The question it raises is, Why does the visual system use more than a single algorithm for calculating relative depth, one when 1-D stimuli are encountered, another when they are not? The relative depth seen between gratings and plaids is generally non-veridical; it does not survive a change in grating orientation (Farell et al.,
2009). By contrast, the relative depth seen between two plaids should survive any change in orientation or disparity direction (within the vertical disparity tolerance range) that conserves the difference between the horizontal disparity components. This is an advantage of coding disparity along a stimulus-independent direction. The visual system does not do this with 1-D stimuli like gratings, but rather codes disparity and orientation jointly (Farell,
2006; Farell et al.,
2009).
The disparities encountered in natural scenes are typically but not generally epipolar. Effects of occlusions and apertures, ocular torsion, and differential perspective, among other factors, make the distribution of disparity directions two-dimensional. Known physiological mechanisms can find binocular matches, within a limited range of magnitudes, whatever the direction of disparity (e.g., Anzai, Ohzawa, & Freeman,
1999; Barlow, Blakemore, & Pettigrew,
1967; LeVay & Voigt,
1988; Maunsell & Van Essen,
1983; Ohzawa & Freeman,
1986; Prince, Pointon, Cumming, & Parker,
2002; von der Heydt, Adorjani, Hänny, & Baumgartner,
1978; see, however, Cumming,
2002). Presumably, the distribution of preferred disparities of these mechanisms has no direct relation to the two-dimensional distribution of disparity directions encountered in natural scenes. Instead, it would be expected to reflect the distribution of component disparities.
It is unlikely that the disparity-projection calculation exists in order to contribute to our perception of lines or gratings in depth (Chai & Farell,
2009). Rather, it is useful for combining the disparities of the 1-D components of a 2-D patterns (Farell,
1998; Patel, Bedell, & Sampat,
2006; Patel et al.,
2003). To arrive at an orientation-invariant disparity, component disparities should be combined along a stimulus-independent disparity axis. Horizontal disparities provide such an axis, and our evidence here shows that horizontal disparities do provide a common metric for comparing the depths of different 2-D patterns, whether their spatial structures and disparity directions are similar or not. However, horizontal pattern disparities are probably not calculated from component disparities directly, but rather from an intermediate computation that yields the two-dimensional pattern disparity vector. This appears computationally easier than the direct route. Data for depth matches between gratings and plaids (Chai & Farell,
2009; Farell et al.,
2009) show that a representation of these two-dimensional pattern disparities exists and is used.