Color constancy mechanisms in virtual reality environments.

Prior research has demonstrated high levels of color constancy in real-world scenarios featuring single light sources, extensive fields of view, and prolonged adaptation periods. However, exploring the specific cues humans rely on becomes challenging, if not unfeasible, with actual objects and lighting conditions. To circumvent these obstacles, we employed virtual reality technology to craft immersive, realistic settings that can be manipulated in real time. We designed forest and office scenes illuminated by five colors. Participants selected a test object most resembling a previously shown achromatic reference. To study color constancy mechanisms, we modified scenes to neutralize three contributors: local surround (placing a uniform-colored leaf under test objects), maximum flux (keeping the brightest object constant), and spatial mean (maintaining a neutral average light reflectance), employing two methods for the latter: changing object reflectances or introducing new elements. We found that color constancy was high in conditions with all cues present, aligning with past research. However, removing individual cues led to varied impacts on constancy. Local surrounds significantly reduced performance, especially under green illumination, showing strong interaction between greenish light and rose-colored contexts. In contrast, the maximum flux mechanism barely affected performance, challenging assumptions used in white balancing algorithms. The spatial mean experiment showed disparate effects: Adding objects slightly impacted performance, while changing reflectances nearly eliminated constancy, suggesting human color constancy relies more on scene interpretation than pixel-based calculations.

Colour Calibration of a Head Mounted Display for Colour Vision Research Using Virtual Reality.

Virtual reality (VR) technology offers vision researchers the opportunity to conduct immersive studies in simulated real-world scenes. However, an accurate colour calibration of the VR head mounted display (HMD), both in terms of luminance and chromaticity, is required to precisely control the presented stimuli. Such a calibration presents significant new challenges, for example, due to the large field of view of the HMD, or the software implementation used for scene rendering, which might alter the colour appearance of objects. Here, we propose a framework for calibrating an HMD using an imaging colorimeter, the I29 (Radiant Vision Systems, Redmond, WA, USA). We examine two scenarios, both with and without using a rendering software for visualisation. In addition, we present a colour constancy experiment design for VR through a gaming engine software, Unreal Engine 4. The colours of the objects of study are chosen according to the previously defined calibration. Results show a high-colour constancy performance among participants, in agreement with recent studies performed on real-world scenarios. Our studies show that our methodology allows us to control and measure the colours presented in the HMD, effectively enabling the use of VR technology for colour vision research.

Perceptually Validated Cross-Renderer Analytical BRDF Parameter Remapping.

Material appearance of rendered objects depends on the underlying BRDF implementation used by rendering software packages. A lack of standards to exchange material parameters and data (between tools) means that artists in digital 3D prototyping and design, manually match the appearance of materials to a reference image. Since their effect on rendered output is often non-uniform and counter intuitive, selecting appropriate parameterisations for BRDF models is far from straightforward. We present a novel BRDF remapping technique, that automatically computes a mapping (BRDF Difference Probe) to match the appearance of a source material model to a target one. Through quantitative analysis, four user studies and psychometric scaling experiments, we validate our remapping framework and demonstrate that it yields a visually faithful remapping among analytical BRDFs. Most notably, our results show that even when the characteristics of the models are substantially different, such as in the case of a phenomenological model and a physically-based one, our remapped renderings are indistinguishable from the original source model.

Forgery detection and value identification of Euro banknotes.

This paper describes both hardware and software components to detect counterfeits of Euro banknotes. The proposed system is also able to recognize the banknote values. Differently than other state-of-the-art methods, the proposed approach makes use of banknote images acquired with a near infrared camera to perform recognition and authentication. This allows one to build a system that can effectively deal with real forgeries, which are usually not detectable with visible light. The hardware does not use any mechanical parts, so the overall system is low-cost. The proposed solution is reliable for ambient light and banknote positioning. Users should simply lean the banknote to be analyzed on a flat glass, and the system detects forgery, as well as recognizes the banknote value. The effectiveness of the proposed solution has been properly tested on a dataset composed by genuine and fake Euro banknotes provided by Italy's central bank.