Vergence eye movements are not essential for stereoscopic depth.

The brain receives disparate retinal input owing to the separation of the eyes, yet we usually perceive a single fused world. This is because of complex interactions between sensory and oculomotor processes that quickly act to reduce excessive retinal disparity. This implies a strong link between depth perception and fusion, but it is well established that stereoscopic depth percepts are also obtained from stimuli that produce double images. Surprisingly, the nature of depth percepts from such diplopic stimuli remains poorly understood. Specifically, despite long-standing debate it is unclear whether depth under diplopia is owing to the retinal disparity (directly), or whether the brain interprets signals from fusional vergence responses to large disparities (indirectly). Here, we addressed this question using stereoscopic afterimages, for which fusional vergence cannot provide retinal feedback about depth. We showed that observers could reliably recover depth sign and magnitude from diplopic afterimages. In addition, measuring vergence responses to large disparity stimuli revealed that that the sign and magnitude of vergence responses are not systematically related to the target disparity, thus ruling out an indirect explanation of our results. Taken together, our research provides the first conclusive evidence that stereopsis is a direct process, even for diplopic targets.

Speed judgments of three-dimensional motion incorporate extraretinal information.

When tracking an object moving in depth, the visual system should take changes of eye vergence into account to judge the object's 3D speed correctly. Previous work has shown that extraretinal information about changes in eye vergence is exploited when judging the sign of 3D motion. Here, we ask whether extraretinal signals also affect judgments of 3D speed. Observers judged the speed of a small target surrounded by a large background. To manipulate extraretinal information, we varied the vergence demand of the entire stimulus sinusoidally over time. At different phases of vergence pursuit, we changed the disparity of the target relative to the background, leading observers to perceive approaching target motion. We determined psychometric functions for the target's approach speed when the eyes were (1) converging, (2) diverging, (3) maximally converged (near), and (4) maximally diverged (far). The target's motion was reported as faster during convergence and slower during divergence but perceived speed was little affected at near or far vergence positions. Thus, 3D speed judgments are affected by extraretinal signals about changes in eye rotation but appear unaffected by the absolute orientation of the eyes. We develop a model that accounts for observers' judgments by taking a weighted average of the retinal and extraretinal signals to target motion.

The Southampton-York Natural Scenes (SYNS) dataset: Statistics of surface attitude.

Recovering 3D scenes from 2D images is an under-constrained task; optimal estimation depends upon knowledge of the underlying scene statistics. Here we introduce the Southampton-York Natural Scenes dataset (SYNS: https://syns.soton.ac.uk), which provides comprehensive scene statistics useful for understanding biological vision and for improving machine vision systems. In order to capture the diversity of environments that humans encounter, scenes were surveyed at random locations within 25 indoor and outdoor categories. Each survey includes (i) spherical LiDAR range data (ii) high-dynamic range spherical imagery and (iii) a panorama of stereo image pairs. We envisage many uses for the dataset and present one example: an analysis of surface attitude statistics, conditioned on scene category and viewing elevation. Surface normals were estimated using a novel adaptive scale selection algorithm. Across categories, surface attitude below the horizon is dominated by the ground plane (0° tilt). Near the horizon, probability density is elevated at 90°/270° tilt due to vertical surfaces (trees, walls). Above the horizon, probability density is elevated near 0° slant due to overhead structure such as ceilings and leaf canopies. These structural regularities represent potentially useful prior assumptions for human and machine observers, and may predict human biases in perceived surface attitude.

Evaluating methods to measure time-to-contact.

Many every-day activities necessitate an estimate of the time remaining until an object will hit us: the time-to-contact (TTC). Observers' skill in estimating TTC has been studied by considering the use and combination of key visual signals (e.g. looming and disparity). However, establishing observers' proficiency in estimating TTC can be complicated, as the variable of interest (time) is typically highly correlated with other signals (e.g. target velocity or displacement). As a result, observers' responses may be based on correlates of TTC rather than on TTC itself. Here we evaluate two widely-used TTC tasks: one absolute task in which observers pressed a button to indicate the estimated TTC, and a relative task in which TTC was judged relative to a reference. We test how a wide range of experimental variables that co-vary with TTC contribute to observers' judgments. We systematically vary the correlation between TTC and its covariates and test how psychophysical judgments are affected. We show that for both absolute and relative estimation tasks, observers' responses are best explained on the basis that they judge TTC rather than one (or more) of its covariates. Our results suggest that relative tasks are preferable when assessing TTC, and we suggest a number of analyses methods to ensure that participants' judgements correspond to the variable under investigation.