News from the Vision.5G project! The first prototype of the use case "digital construction progress control" is now ready.
Good news from the classroom! The WDR climate app recently won silver at the Deutscher Digital Award. This award not only confirms the thematic relevance of the app, but also the innovative implementation using augmented reality technology, which impressed the jury.
We are proud to announce that our project PraktikApp will take part at this year’s IFA NEXT from the 02.09 to 06.09 in Berlin.
In the interactive participatory dance performance 1250 Mb/s produced by fabien prioville dance company and technically developed by MIREVI, the audience enters into a physical game with the dancers, making the process of data collection tangible.
Face-to-face conversation in Virtual Reality (VR) is a challenge when participants wear head-mounted displays (HMD). A significant portion of a participant’s face is hidden and facial expressions are difficult to perceive. Past research has shown that high-fidelity face reconstruction with personal avatars in VR is possible under laboratory conditions with high-cost hardware. In this paper, we propose one of the first low-cost systems for this task which uses only open source, free software and affordable hardware.
In what follows we will compare the two game engines Unity and Unreal with respect to the realization of an augmented reality (AR) application. The comparison is based on the visual quality and the technological possibilities of our current state of development and experience.
The objective of our research is to enhance the creation of interactive environments such as in VR applications. An interactive environment can be produced from a point cloud that is acquired by a 3D scanning process of a certain scenery. The segmentation is needed to extract objects in that point cloud to, e.g., apply certain physical properties to them in a further step. It takes a lot of effort to do this manually as single objects have to be extracted and post-processed. Thus, our research aim is the real-world, cross-domain, automatic, semantic segmentation without the estimation of specific object classes.
Three-dimensional capture of faces with personal expressions for facial reconstruction under a head-mounted display.
We propose a method to segment a real world point cloud as perceptual grouping task (PGT) by a deep reinforcement learning (DRL) agent. A point cloud is divided into groups of points, named superpoints, for the PGT. These superpoints should be grouped to objects by a deep neural network policy that is optimised by a DRL algorithm.
The segmentation of point clouds is conducted with the help of deep reinforcement learning (DRL) in this contribution. We want to create interactive virtual reality (VR) environments from point cloud scans as fast as possible. These VR environments are used for secure and immersive trainings of serious real life applications such as the extinguishing of a fire. It is necessary to segment the point cloud scans to create interactions in the VR
Being able to teleport people and objects or even entire rooms is a long-cherished dream and has been shown in many science fiction movies. Thanks to innovative technologies, it is now possible to scan rooms and people as well as to digitize and “teleport” them by sending the scans to a remote location.
Our goal is to create realistic 3D images of objects or rooms. For this purpose, we use the laser scanner Faro Focus S70, which can capture anything visible in a sphere with a radius of up to 70 meters. Whenever we scan a room, we also move along the walls and take overlapping photographs. Overall, depending on the size of the room or object, we collect between 600 and 1500 pictures to ensure that we obtain enough material in a single scanning process.
In this research project, we try to find out what kind of added value AR (augmented reality) may offer for a smart-home application. To answer this question, we have created a 3D model of an existing sitting area with a sofa and we work with smart-home sensors that enable us to control various aspects.
With today’s technology it has become possible to generate and control personalized as well as authentic avatar faces in 3D for social Virtual Reality (VR) applications, as Lombardi et al. [LSSS18] have recently shown. Creating a personalized avatar with facial expressions is expensive in terms of time, computational power and hardware.
The first modelling applications for Virtual Reality were only sketch-based modeller or simple clay modeller. But ClayMore is more than just only clay.