Seeing through transparent layers

Abstract

The human visual system is remarkably good at decomposing local and global deformations in the flow of visual information into different perceptual layers, a critical ability for daily tasks such as driving through rain or fog or catching that evasive trout. In these scenarios, changes in the visual information might be due to a deforming object or deformations due to a transparent medium, such as structured glass or water, or a combination of these. How does the visual system use image deformations to make sense of layering due to transparent materials? We used eidolons to investigate equivalence classes for perceptually similar transparent layers. We created a stimulus space for perceptual equivalents of a fiducial scene by systematically varying the local disarray parameters reach and grain. This disarray in eidolon space leads to distinct impressions of transparency, specifically, high reach and grain values vividly resemble water whereas smaller grain values appear diffuse like structured glass. We asked observers to adjust image deformations so that the objects in the scene looked like they were seen (a) under water, (b) behind haze, or (c) behind structured glass. Observers adjusted image deformation parameters by moving the mouse horizontally (grain) and vertically (reach). For two conditions, water and glass, we observed high intraobserver consistency: responses were not random. Responses yielded a concentrated equivalence class for water and structured glass.

Motion direction, luminance contrast, and speed perception: An unexpected meeting

“…Due to water droplets in air, which is even augmented in fog, objects having lower luminance contrast are perceived as farther in space (O'Shea et al, 1994;Pretto et al, 2012). Observers consider the effects of a water medium on the deformation in shape of an object (Dövencioglu, van Doorn, Koenderink, & Doerschner, 2018), and take into account buoyancy to estimate object motion (Castillo, Waltzer, & Kloos, 2017;Masin & Rispoli, 2010). For example, when we drop a lump of sugar into a cup of tea or a pebble in an aquarium, we expect that it will move slower in the aqueous medium than when in mid-air.…”

The effect of water immersion on vection in virtual reality

“…Another factor to pay attention to in future studies resides in the fact that in the Water condition two layers of transparent material sit between the screen of the phone and the eyes of the participants, namely the transparent plastic of the diving mask and a layer of water between the mask and the phone. These two layers are not present in the Ground condition and their impact should be investigated while tapping into research on vision through transparent layers 73 and refractive structure 74 .…”

Softness and weight from shape: Material properties inferred from local shape features

“…In addition to objects created with ShapeToolbox, we included eight Glavens ( Phillips, Casella, & Egan, 2016 ) ( Figure 2 H) and 12 three-dimensional scans of bell peppers (Capsicum annuum) ( Norman & Phillips, 2016 ) ( Figure 2 I) (Glavens and bell peppers are both licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License; http://creativecommons.org/licenses/by-nc-sa/4.0/ ). Both types of stimuli were used in a number of previous studies (e.g., Dövencioglu, van Doorn, Koenderink, & Doerschner, 2018 ; Ennis & Doerschner, 2019 ; Norman, Phillips, Cheeseman, Thomason, Ronning, Behari, Kleinman, Calloway, & Lamirande, 2016 ; Norman, Norman, Clayton, Lianekhammy, & Zielke, 2004 ; Phillips et al, 2009 ). Altogether, our set comprised 479 stimuli.…”

“…studies (e.g., Dövencioglu, van Doorn, Koenderink, & Doerschner, 2018;Ennis & Doerschner, 2019;Norman, Phillips, Cheeseman, Thomason, Ronning, Behari, Kleinman, Calloway, & Lamirande, 2016;Norman, Norman, Clayton, Lianekhammy, & Zielke, 2004;Phillips et al, 2009). Altogether, our set comprised 479 stimuli.…”