The perception of three-dimensional contours and the effect of luminance polarity and color change on their detection

Abstract

In the present study we investigated the detectability of three-dimensional (3D) cocircular contours defined by binocular disparity and established the influence of a number of stimulus factors to their perception. In Experiment 1 we examined the depth range over which local elements are grouped in depth, and whether contour detectability systematically changed with the degree to which they are oriented in depth. We found that increasing the orientation of curved contours in depth improved detection performance. In Experiment 2, we examined the degree to which contour detection was disrupted by varying their continuity in depth by jittering the local depth position of contour elements. Detection performance declined with the increasing displacement of local contour elements in depth away from the depth orientation of the contour. Experiments 3 and 4 ascertained whether a detection advantage is afforded to 3D contours defined by local variations in luminance polarity and color. Local color and polarity differences can disrupt the two-dimensional grouping of local contour elements on the basis of similarity, but we tested whether continuity in depth facilitates grouping of contour elements differing in polarity and color. We found no detection advantage for 3D contours defined by local color and polarity variations, suggesting binocular disparity does not facilitate grouping in depth when local elements differ in color and polarity. These findings further suggest the visual system uses binocular disparity to detect contours, but is likely to involve systems tuned to luminance polarity and color.

Contours of Vision: Towards a Compositional Semantics of Perception

“…This model offers a precise, parameterized definition of the Gestalt rule of 'good continuation', which states that for a set of elements to be seen as a cohesive contour, their represented positions and orientations must approximately conform to a smooth curve. The model generalizes beyond artificial path detection stimuli, explaining our abilities to represent contours that are fully connected and naturalistic (Geisler, Perry et al, [2001]; Elder and Goldberg, [2002]), extended in depth (Hess and Field, [1995]; Hess, Hayes et al, [1997]; Khuu et al, [2016]), partially occluded or camouflaged (Kellman, Garrigan and Shipley, [2005]), and which contain corners (Persike and Meinhardt, [2016]). 13 As stated, the association field constitutes a constraint on the pairwise combination of contour representations.…”

The Effect of Local Orientation Change on the Detection of Contours Defined by Constant Curvature: Psychophysics and Image Statistics

“…However, if contour detection operated in a pairwise fashion, then collinear placements of end elements will lead to greater contour sensitivity. These testing procedures offer direct way of assessing the specificity of curved contour processing (beyond simply characterizing their detectability as a function of contour angle, see Pettet, 1999; Beaudot and Mullen, 2003; Khuu et al, 2016), as it directly assesses the propagation of curvature structure along the extent of the contour to affect the coding of elements at its ends.…”

“…The curvature that characterizes such objects might signal a meaningful unit that perhaps conforms to the Gestalt principles of “continuity” and “smoothness” and might contribute to “closure”—a tendency to perceive a whole stimulus from incomplete parts. Indeed, previous studies have shown that the visual system is preferentially sensitive to the curvature characteristics of contours (e.g., Pettet, 1999; Khuu et al, 2016). For example, Pettet (1999) showed that path smoothness and the angle of curvature were important in the perception of curved contours as they directly facilitate contour detection and sensitivity.…”

“…In visual scenes, contours are a collection of spatially linked line elements that are associated based on a small number of common properties such as regular continuity, orientation, depth, closure, and proximity (see e.g., Marr, 1982; Field et al, 1993; Kovacs and Julesz, 1993; Khuu et al, 2015, 2016). Spatial contours are salient attributes of the visual scene as they may signify spatial layout, which contributes to defining the boundaries of objects and perceptual organization (Marr, 1982).…”

Good continuation in 3D: the neurogeometry of stereo vision

“…The main application will be a good continuation model in three dimensions that is analogous to the models of contour organization in two dimensions. We will develop ad hoc mathematical instruments, supported by a number of neural and psychophysical investigations (Malach et al, 1993;Uttal, 2013;Wilcox, 2014, 2015;Khuu et al, 2016;Scholl et al, 2022).…”