ECVP 2019 ESR Abstracts

ECVP 2019 ESR Abstracts

The ECVP have now released the full abstracts of the attendees to the conference in Leuven. Below you will find the abstracts submitted by DyViTo ESRs. To see the full abstract book, including the abstracts that involve DyViTo Supervisors and friends of the project, please use this link.

Scale ambiguities in material recognition
Jacob R. Cheeseman*, Filipp Schmidt, Roland W. Fleming
Justus Liebig University Giessen

As a rule, observers can reliably identify the material properties of surfaces. Here, we investigated exceptions to this rule using a set of 87 photographs of materials (e.g., water, sand, stone, metal, wood) that appear to belong to different material classes depending on their apparent distance from the viewer. In three experiments, participants viewed each image and provided a categorical judgement of the depicted material, and a quantitative estimate of the distance between the camera and surface. Experiment 1 manipulated interpretations of these images by instructing two groups of participants to imagine a small or large distance between the camera and surface, while a third control group received no such instruction. In Experiments 2 and 3 interpretations were manipulated by providing visual cues for scale (e.g., objects of familiar size), which were presented alongside the target image or digitally inserted into the image. Results indicate that these manipulations can cause identical images to appear to belong to different material classes (e.g., water vs. marble), and that susceptibility to context information (i.e., material ambiguity) correlates with higher variability in distance estimates. Under challenging conditions, therefore, the recognition of some materials is vulnerable to simple manipulations of apparent scale.

Colour Variations within Light Fields: Interreflections and Colour Effects
Cehao Yu* (1), Elmar Eisemann (2), Sylvia Pont (1)
1: Perceptual Intelligence lab, TUDelft; 2: Computer Graphics and Visualization Group, TUDelft

The human visual system incorporates knowledge about local chromatic and lightness effects of interreflections (Bloj et al., Nature, 1999). Here we study basic principles behind chromatic effects of interreflections using computational modelling and photometric measurements. The colour of interreflections varies as a function of the number of bounces they went through. Using a computational model we found that those colour variations can show brightness, saturation and even hue shifts. Using a chromatic Mach Card, a concave folded card with both sides made of the same colour, we demonstrated those three types of colour effects empirically. Finally, we tested the effects of such coloured interreflections on light fields in 3D spaces. Via cubic spectral illuminance measurements in both computer simulations and full mock up room settings under different furnishing scenarios we measure the chromatic variations of first order properties of light fields. The types of chromatic variations were found to depend systematically on furnishing colour, lighting and geometry, as predicted, and also vary systematically within the light field, and thus throughout the space. We will next compare the physical light fields with visual light fields (including chromatic properties) and test perceived material colours, for (combinations of) the three types of effects.

Visual and haptic softness dimensions
Müge Cavdan* (1), Knut Drewing (1), Katja Doerschner (1,2,3)
1: Justus Liebig University Giessen, Germany; 2: Department of Psychology, Bilkent University, Ankara, Turkey; 3: National Magnetic Resonance Research Center, Bilkent University, Ankara, Turkey

When investigating visually or haptically perceived softness of materials researchers have typically equated softness with compliance. However, softness entails more aspects than this single dimension: a rabbit’s fur is soft in a different way than sand on Siesta beach and both’s softness is not necessarily related to the materials’ compliance. Here we investigated the dimensionality of perceived softness in visual and haptic domains. We asked participants to rate various materials on different adjectives. In the haptic experiment, participants were blindfolded and rated materials after haptically exploring them, whereas in the visual experiment they made the same ratings while looking at close up images of the same materials used in the haptic experiment. Principal component analyses revealed that both haptic and visual perception of softness are similarly organized in perceptual space, both containing dimensions of granularity, visco-elasticity, and deformability. However, furriness existed only in the haptic experiment. Moreover, the explained variance was higher in the haptic experiment, which suggests that the perceived dimensions of softness might be more accessible through haptic exploration than by looking at images of materials. Overall, these results contribute to our understanding of how visual and haptic information about material properties are processed and integrated.

Recognising materials over time
Ellen E M De Korte* (1), Andrew J Logan (2), Marina Bloj (1)
1: School of Optometry and Vision Science, University of Bradford, United Kingdom; 2:Department of Vision Sciences, Glasgow Caledonian University, United Kingdom

Materials change over time; colours fade and surfaces are scratched. These changes alter the retinal input and yet we still recognise them as the same material. When textiles are washed and laid out to dry we still identify them as the same fabric even though their colour visibly changes. The present study evaluated the appropriateness of an existing calibrated photograph set as a stimulus for studying the perception of appearance changes of materials over time. Participants (N = 4) reported which of the 2 pairs of images shown displayed the largest perceptual difference. Images were blocked (210 trials per block and participant) by material (Banana, Copper, Granite, Quilted Paper). Individual observers’ perceptual scales, estimated with Maximum Likelihood Difference Scaling via the General Linear Model estimation method, for each material were similar and showed that some, but not all, photographs were perceptually distinct. Thus, the calibrated photographs seem suitable for our purposes. Next steps will include image-based manipulations to establish which parameters drive the development of perceptual scales. Specifically, this will involve converting images to grayscale and manipulate image marks, such as brown staining in Banana images, in order to test the effects of colour and characteristic marks, respectively.

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