Markus Tatzgern

Irina Paraschivoiu, Thomas Layer-Wagner, Klaus Neundlinger et al.

We explore how narrative-driven asymmetric VR experiences can support the development of teamwork-related knowledge, skills, and attitudes (KSAs), such as communication, coordination, trust, and reflexivity. We present the design and evaluation of a tablet-based VR training experience structured around spatial separation, tool asymmetry, and interdependent tasks that require verbal coordination. The experience was designed based on interviews with HR professionals and mapped to a framework of established KSAs. We conducted a co-located user study (N=16) that involved two consecutive collaborative scenarios. Our findings show that users adapted dynamically using verbal exchange, role negotiation, and shared representations to coordinate under asymmetric conditions. We also observed active application of teamwork KSAs. Based on our insights, we present design recommendations for creating effective immersive team training interventions.

Peter Mohr, Markus Tatzgern, Jens Grubert et al.

Handheld Augmented Reality commonly implements some variant of magic lens rendering, which turns only a fraction of the user's real environment into AR while the rest of the environment remains unaffected. Since handheld AR devices are commonly equipped with video see-through capabilities, AR magic lens applications often suffer from spatial distortions, because the AR environment is presented from the perspective of the camera of the mobile device. Recent approaches counteract this distortion based on estimations of the user's head position, rendering the scene from the user's perspective. To this end, approaches usually apply face-tracking algorithms on the front camera of the mobile device. However, this demands high computational resources and therefore commonly affects the performance of the application beyond the already high computational load of AR applications. In this paper, we present a method to reduce the computational demands for user perspective rendering by applying lightweight optical flow tracking and an estimation of the user's motion before head tracking is started. We demonstrate the suitability of our approach for computationally limited mobile devices and we compare it to device perspective rendering, to head tracked user perspective rendering, as well as to fixed point of view user perspective rendering.