The effect of retinal illuminance and chromatic imbalance on stereopsis

This study was designed to determine the effect on stereopsis of interocular retinal chromatic and illuminance imbalance in 30 subjects with normal binocularity. A Randot Circle Stereotest viewed through polarizing glasses was the control condition. In each of the other three conditions, illuminance and chromatic imbalances were created by combinations of neutral density filters, red and green filters, and polarizing filters. The effect of each of four experimental conditions on stereopsis was determined by comparing total stereo judgement errors on the Randot Circle Stereotest. Total average flux through the filter combinations was held constant by adjusting the luminance level of light reflected from the target. The chromatic imbalance created by the red-green filters significantly increased the number of stereo judgement errors (37%, p \u3c 0.05); however, the illuminance imbalance (0.2 log units) created by the red-green filters did not significantly increase the number of errors (2.9%, p \u3c 0.65); finally, the combined illuminance and chromatic imbalance created by the red-green filters significantly increased the error frequency (46%, p \u3c 0.05). The chromatic imbalance caused by red-green glasses significantly degrades stereopsis, whereas the illuminance imbalance caused by these filters has little effect on stereopsis

Correcting the chromatic anisometropia of red-green glasses and its effect on stereoaccuracy

Negative effects on stereoaccuracy induced by commonly used red-green filters have been a subject of recent investigation1. This study was designed to determine if correcting, with lenses, the chromatic anisometropia induced by these red-green filters could increase the accuracy of stereopsis. The lens power difference needed to correct the chromatic anisometropia was found to be 0.37°, divided between the two eyes. In the control condition the subjects viewed the Randot Circle Stereotest with only the required polarizing glasses. One of the remaining two test conditions used the polarizers in combination with red-green filters, while for the other condition the chromatic anisometropia from the red-green filters was corrected with appropriate lenses. The amount of light transmitted by the filters was kept constant. The chromatic anisometropia correction over the red-green filters significantly reduced stereopsis errors induced by the red-green filters alone (21%, p \u3c 0.05). However, the correction only partially restored stereopsis to control values. A mild anisometropic correction added to the red-green glasses could help improve stereopsis in most individuals

Texture Segregation, Surface Representation, and Figure-ground Separation

A widespread view is that most of texture segregation can be accounted for by differences in the spatial frequency content of texture regions. Evidence from both psychophysical and physiological studies indicate, however, that beyond these early filtering stages,there are stages of 3-D boundary segmentation and surface representation that are used to segregate textures. Chromatic segregation of element-arrangement patterns as studied by Beck and colleagues - cannot be completely explained by the filtering mechanisms previously employed to account for achromatic segregation. An element arrangement pattern is composed of two types of elements that are arranged differently in different image regions (e.g., vertically on top and diagonally on bottom). FACADE theory mechanisms that have previously been used to explain data about 3-D vision and figure-ground separation are here used to simulate chromatic texture segregation data, in eluding data with equiluminant elements on dark or light homogenous backgrounds, or backgrounds composed of vertical and horizontal dark or light stripes, or horizontal notched stripes. These data include the fact that segregation of patterns composed of red and blue squares decreases with inereasing luminance of the interspaces. Asymmetric segregation properties under 3-D viewing conditions with the cquiluminant element;; dose or far arc abo simulated. Two key model properties arc a spatial impenetrability property that inhibits boundary grouping across regions with noncolinear texture elements, and a boundary-surface consistency property that uses feedback between boundary and surface representations to eliminate spurious boundary groupings and separate figures from their backgrounds.Office of Naval Research (N00014-95-1-0409, N00014-95-1-0657, ONR N00014-91-J-4100); CNPq/Brazil (520419/96-0); Air Force Office of Scientific Research (F49620-92-J-0334

Boundary, Brightness, and Depth Interactions During Preattentive Representation and Attentive Recognition of Figure and Ground

This article applies a recent theory of 3-D biological vision, called FACADE Theory, to explain several percepts which Kanizsa pioneered. These include 3-D pop-out of an occluding form in front of an occluded form, leading to completion and recognition of the occluded form; 3-D transparent and opaque percepts of Kanizsa squares, with and without Varin wedges; and interactions between percepts of illusory contours, brightness, and depth in response to 2-D Kanizsa images. These explanations clarify how a partially occluded object representation can be completed for purposes of object recognition, without the completed part of the representation necessarily being seen. The theory traces these percepts to neural mechanisms that compensate for measurement uncertainty and complementarity at individual cortical processing stages by using parallel and hierarchical interactions among several cortical processing stages. These interactions are modelled by a Boundary Contour System (BCS) that generates emergent boundary segmentations and a complementary Feature Contour System (FCS) that fills-in surface representations of brightness, color, and depth. The BCS and FCS interact reciprocally with an Object Recognition System (ORS) that binds BCS boundary and FCS surface representations into attentive object representations. The BCS models the parvocellular LGN→Interblob→Interstripe→V4 cortical processing stream, the FCS models the parvocellular LGN→Blob→Thin Stripe→V4 cortical processing stream, and the ORS models inferotemporal cortex.Air Force Office of Scientific Research (F49620-92-J-0499); Defense Advanced Research Projects Agency (N00014-92-J-4015); Office of Naval Research (N00014-91-J-4100

Advancing a new theory of stereopsis: Reply to Rogers (2019)

Vishwanath (2014) presented analyses and proposed conjectures aimed at a unified understanding of both qualitative and quantitative aspects of stereopsis in pictorial and natural (real-world) 3-dimensional (3D) vision. A recent commentary by Rogers (2019) conceded the key argument in the article, that stereopsis can be induced in the absence of binocular disparity and motion parallax but criticized the wider analyses and conjectures. Rogers argued that a focus on visual appearance and qualitative aspects of 3D perception is unproductive and that the analysis of pictorial space perception adds little to our wider understanding of 3D vision. I argue here that the critique is not persuasive as it misconstrues the distinction between qualitative and quantitative aspects of perception and its claims regarding pictorial depth perception rely on introspections that often do not align with the empirical record. I reaffirm that an integrative focus on both qualitative and quantitative aspects of both pictorial and natural 3D perception is crucial for advancing an understanding of the complex phenomenon of stereopsis.PostprintPeer reviewe

Colour Helmholtz Stereopsis for Reconstruction of Complex Dynamic Scenes

Helmholtz Stereopsis (HS) is a powerful technique for reconstruction of scenes with arbitrary reflectance properties. However, previous formulations have been limited to static objects due to the requirement to sequentially capture reciprocal image pairs (i.e. two images with the camera and light source positions mutually interchanged). In this paper, we propose colour HS-a novel variant of the technique based on wavelength multiplexing. To address the new set of challenges introduced by multispectral data acquisition, the proposed novel pipeline for colour HS uniquely combines a tailored photometric calibration for multiple camera/light source pairs, a novel procedure for surface chromaticity calibration and the state-of-the-art Bayesian HS suitable for reconstruction from a minimal number of reciprocal pairs. Experimental results including quantitative and qualitative evaluation demonstrate that the method is suitable for flexible (single-shot) reconstruction of static scenes and reconstruction of dynamic scenes with complex surface reflectance properties

Filling-in the Forms: Surface and Boundary Interactions in Visual Cortex

Defense Advanced Research Projects Agency and the Office of Naval Research (NOOOI4-95-l-0409); Office of Naval Research (NOOO14-95-1-0657)

Artificially induced aniseikonic effects on stereomobilization

Aniseikonia affects binocular visual function. The effects of aniseikonia on stereomobilization, however, have not been studied. A Latin Square design was used to test the effects aniseikonia has on stereomobilization. Results indicate that increased aniseikonia decreased stereomobilization. Also, reduced presentation time decreased stereomobilization

From Stereogram to Surface: How the Brain Sees the World in Depth

When we look at a scene, how do we consciously see surfaces infused with lightness and color at the correct depths? Random Dot Stereograms (RDS) probe how binocular disparity between the two eyes can generate such conscious surface percepts. Dense RDS do so despite the fact that they include multiple false binocular matches. Sparse stereograms do so even across large contrast-free regions with no binocular matches. Stereograms that define occluding and occluded surfaces lead to surface percepts wherein partially occluded textured surfaces are completed behind occluding textured surfaces at a spatial scale much larger than that of the texture elements themselves. Earlier models suggest how the brain detects binocular disparity, but not how RDS generate conscious percepts of 3D surfaces. A neural model predicts how the layered circuits of visual cortex generate these 3D surface percepts using interactions between visual boundary and surface representations that obey complementary computational rules.Air Force Office of Scientific Research (F49620-01-1-0397); National Science Foundation (EIA-01-30851, SBE-0354378); Office of Naval Research (N00014-01-1-0624