Biases in three–dimensional structure–from–motion arise from noise in the early visual system

Abstract

The projected pattern of retinal-image motion supplies the human visual system with valuable information about properties of the three-dimensional environment. How well three-dimensional properties can be recovered depends both on the accuracy with which the early motion system estimates retinal motion, and on the way later processes interpret this retinal motion. Here we combine both early and late stages of the computational process to account for the hitherto puzzling phenomenon of systematic biases in three-dimensional shape perception. We present data showing how the perceived depth of a hinged plane (`an open book') can be systematically biased by the extent over which it rotates. We then present a Bayesian model that combines early measurement noise with geometric reconstruction of the three-dimensional scene. Although this model has no in-built bias towards particular threedimensional shapes, it accounts for the data well. Our analysis suggests that the biases stem largely from the geometric constraints imposed on what three-dimensional scenes are compatible with the (noisy) early motion measurements. Given these ¢ndings, we suggest that the visual system may act as an optimal estimator of three-dimensional structure-from-motion.

Systematic biases in adult color perception persist despite lifelong information sufficient to calibrate them

“…However, while the well-known mechanisms and anatomy of low-level color processes makes our example accessible to precise measurements and modeling, spatial perception is much more complex to investigate. Moreover, spatial distortions can actually reflect an optimal combination of available evidence (Hogervorst & Eagle, 1998). Present literature investigating color perception from an ideal observer perspective (Brainard et al, 2006;Brainard, Williams, & Hofer, 2008;Geisler & Kersten, 2002) does not suggest that a parallel argument applies in the case of color constancy across the visual field.…”

A new theory of structure-from-motion perception

“…Under orthographic projection, instead, thresholds increased with size until reaching random performance levels. On another study but using the same stimuli, Hogervorst and Eagle (1998) found a pattern of misperceptions that depended on stimulus size and rotation angle. They showed that errors in the estimate of speeds and accelerations could explain the pattern of misperceptions.…”

“…Regarding perspective effects, Eagle and Hogervorst (1999) found that shape discrimination thresholds decreased with stimulus size under perspective projection, but under orthographic projection, thresholds increased. Regarding the effects of accelerations, Hogervorst and Eagle (1998, 2000) showed that errors in the estimate of speeds and accelerations could explain some pattern of misperceptions in SFM.…”

“… 10 An anonymous reviewer noted an interesting parallel between the template model and the model of Hogervorst and Eagle (1998). To quote the reviewer, “When the templates reflect the prior probability of shapes and motions that can occur (which is likely) the activity of the template cells resembles the posterior probability.…”

“…To quote the reviewer, “When the templates reflect the prior probability of shapes and motions that can occur (which is likely) the activity of the template cells resembles the posterior probability. Moreover, the model by Hogervorst and Eagle (1998) calculates for each combination of shape and motion parameters a probability that depends on the match between the optic flow (the stimulus) and the flow resulting from a 3-D object and motion (similar to a template). In the template model, each combination is covered by a template cell.”…”