Using visual direction in three-dimensional motion perception

Abstract

The eyes receive slightly different views of the world, and the differences between their images (binocular disparity) are used to see depth. Several authors have suggested how the brain could exploit this information for three-dimensional (3D) motion perception, but here we consider a simpler strategy. Visual direction is the angle between the direction of an object and the direction that an observer faces. Here we describe human behavioral experiments in which observers use visual direction, rather than binocular information, to estimate an object's 3D motion even though this causes them to make systematic errors. This suggests that recent models of binocular 3D motion perception may not reflect the strategies that human observers actually use.

Sensory uncertainty leads to systematic misperception of the direction of motion in depth

“…See the individual experimental sections for the corresponding luminance values. The majority of the data points fall above the identity line, including the group mean (± −1 SEM), which is consistent with the predicted results if the uncertainty in the estimates of the two velocity components is correlated and both factor into the variance in judgment errors previously that 2D motion appears slower under high-noise conditions, but that even under low-noise conditions 3D motion appears to be systematically laterally biased-i.e., observers report motion as moving more sideways (Harris & Dean, 2003;Welchman et al, 2004;Harris & Drga, 2005;Gray et al, 2006;Poljac et al, 2006;Lages, 2006;Rushton & Duke, 2007;Welchman et al, 2008;Duke & Rushton, 2012). We do not find evidence for such bias in our data.…”

“…The common source of sensory information (i.e., the retinal motion) used to derive these estimates predicts a correlation between the measures such that uncertainty in the motion in depth direction should be associated with greater variability in lateral judgments. Previous work has reported that observers do not rely on the z-component of motion when reporting trajectory direction (Harris & Dean, 2003;Harris & Drga, 2005). This would result in the two measures not being correlated.…”

“…Indeed, previous work has reported systematic biases in the estimation of both real and virtual object motion in depth, such that objects appear to move more sideways (Harris & Dean, 2003;Welchman, Tuck, & Harris, 2004;Harris & Drga, 2005;Gray, Regan, Castaneda, & Sieffert, 2006;Poljac, Neggers, & van den Berg, 2006;Lages, 2006;Rushton & Duke, 2007;Welchman, Lam, & Bülthoff, 2008;Duke & Rushton, 2012). This lateral bias is thought to arise based on the geometry of 3D motion perception and the mechanism for 2D speed perception described above (Welchman et al, 2008).…”

Motion and disparity processing informs Bayesian 3D motion estimation

“…Motion and disparity processing informs Bayesian 3D motion estimation Welchman et al (1) propose a Bayesian model that combines a velocity prior for slow motion (2, 3) with approximations of lateral velocity V x and velocity in depth V z to model biased perception of 3D motion trajectories in the x-z plane (3,4). Although decomposing a motion vector into orthogonal components may be mathematically convenient it raises the question of why the visual system should approximate these velocities in the first place.…”

Optic variables used to judge future ball arrival position in expert and novice soccer players

“…Many studies have thus focused on the temporal aspects of interception-namely, the detection and use of time-to-contact information (Bootsma, Fayt, Zaal, & Laurent, 1997;Lee, 1998). Fewer studies have focused on the identification of the information, which specifies "where" the object is going to arrive (but see Gray & Regan, 2006;Harris & Drga, 2005;Peper et al, 1994).…”