The recent success of Machine Learning encouraged research using artificial neural networks (NNs) in computer graphics. A good example is the bidirectional texture function (BTF), a data-driven representation of surface materials that can encapsulate complex behaviors that would otherwise be too expensive to calculate for real-time applications, such as self-shadowing and interreflections. We propose two changes to the state-of-the-art using neural networks for BTFs, specifically NeuMIP. These changes, suggested by recent work in neural scene representation and rendering, aim to improve baseline quality, memory footprint, and performance. We conduct an ablation study to evaluate the impact of each change. We test both synthetic and real data, and provide a working implementation within the Mitsuba 2 rendering framework. Our results show that our method outperforms the baseline in all these metrics and that neural BTF is part of the broader field of neural scene representation. Project website: https://traverse-research.github.io/NeuBTF/.
DOCUMENT
One of the key challenges in the rapid technological advance of Virtual Reality (VR) and Mixed Reality (MR) concerns the design of collaborative experiences. VR systems do not readily support team collaboration because they tend to focus on individual experiences and do not easily facilitate naturalistic collaboration. MR environments provide solutions for collaborative experiences, but establishing smooth communication between hardware components and software modules faces a major hurdle. This paper presents the background to and main challenges of an ongoing project on collaboration in an MR lab, aiming to design a serious 'team collaboration' game. To this end, we utilized a common game engine to engineer a cost-effective solution that would make the game playable in a configuration operated by WorldViz and Volfoni equipment. Evaluation of various solutions in the development process found a Unity 3D Cluster Rendering Beta solution to be the most cost-effective and successful.
DOCUMENT
One of the key challenges in the rapid technological advance of Virtual Reality (VR) and Mixed Reality (MR) concerns the design of collaborative experiences. VR systems do not readily support team collaboration because they tend to focus on individual experiences and do not easily facilitate naturalistic collaboration. MR environments provide solutions for collaborative experiences, but establishing smooth communication between hardware components and software modules faces a major hurdle. This paper presents the background to and main challenges of an ongoing project on collaboration in an MR lab, aiming to design a serious 'team collaboration' game. To this end, we utilized a common game engine to engineer a cost-effective solution that would make the game playable in a configuration operated by WorldViz and Volfoni equipment. Evaluation of various solutions in the development process found a Unity 3D Cluster Rendering Beta solution to be the most cost-effective and successful.
DOCUMENT
There still remains many challenges in creating an effective and efficient cloud gaming operation able to handle the new release games of today. There are also many existing paths to creating a cloud gaming architecture. In this paper some of the different approaches, that are beyond that of just remote rendering, are analysed giving insight into the operational approach of each technology. Currently there is a growing number of initiatives in cloud game architectures that vary in significant ways. Although there are many varying technologies, with a lot of promises, the ultimate goal of a cloud game engine is something unique to what has been before. It really is about providing a modular and scalable approach but within a controllable and sandbox like environment.
DOCUMENT
One major drawback of deception detection is its vulnerability to countermeasures, whereby participants wilfully modulate their physiological or neurophysiological response to critical guilt-determining stimuli. One reason for this vulnerability is that stimuli are usually presented slowly. This allows enough time to consciously apply countermeasures, once the role of stimuli is determined. However, by increasing presentation speed, stimuli can be placed on the fringe of awareness, rendering it hard to perceive those that have not been previously identified, hindering the possibility to employ countermeasures. We tested an identity deception detector by presenting first names in Rapid Serial Visual Presentation and instructing participants to lie about their own identity. We also instructed participants to apply a series of countermeasures. The method proved resilient, remaining effective at detecting deception under all countermeasures.
MULTIFILE
De Digitale Universiteit (DU) performed a quickscan to determine the usability of the IMS Question and TestInteroperability (QTI) specification as a format to store questions and tests developed for and by the consortium. The original report is available in Dutch from the website of De Digitale Universiteit and an unofficial English translation of that report can be downloaded. In October 2003, Canvas Learning Ltd., developers of the Canvas Canvas Learning Author and Canvas Learning Player responded to the Quickscan by sending their Canvas Flash player which could also render the test questions developed for the Quickscan. The Canvas Learning Player hadn't been tested as part of the original Quickscan because none of the partners within De Digitale Universiteit was using the application at that time. This addendum contains a short overview of the results of the tests for the Flash player as it was provided by Canvas Learning Ltd. All tests have been conducted by the author of the quickscan using the original test set. The set and the player used can be downloaded as a SCORM compliant package.
DOCUMENT
