Grasping is one of the most important factors of human evolution and even young children start to explore the world by dominantly using touch. However, current interaction technologies suffer from an imbalance between visual and haptic stimulation. Shape-changing interfaces are one line of research addressing this issue. Unfortunately, these systems are often very complex and difficult to replicate. This is not the case for Elastic Displays that have low mechanical complexity and utilize consumer hardware. Albeit their simple setup, neither off-the-shelf hardware for research purposes or instructions on how to assemble such systems are available. This hampers open science and the replication of research results. In this paper, we describe our experiences on constructing an Elastic Display. We present lessons learned from several field tests and the final requirements of the setup. Moreover, we introduce an open source documentation of the hardware assembly instructions, which integrates with a previously published open source software framework. With both hardware and software now being readily available, novel application concepts for Elastic Displays can be explored by a broad community.

The leading motive of the research demo is the utilization of the Augmented Virtuality technology and in particular the egocentric representation of real body parts in virtual and immersive environments. In this context, a prototypical application was developed, which superimposes the current view of the user's hands on the virtual scene in real-time. This is achieved in form of a captured video stream. Advantages compared to virtual avatars arise from the detailed and individual representation of the user's body and the saving of complex tracking hardware. Due to the integration of a toolbox, the visual appearance of the video overlay is highly customizable.

The established method of representing three-dimensional space on a two-dimensional surface involves camera based, point of regard systems, comparable in design to the early “camera obscura”. However, geometrical limitations of such models lead to distortions of perspective when projected. This research investigated the influence of single- versus multi-perspectives on aesthetic choices within one image. A clear perceptual bias towards multi-perspective images was found, additionally supported by an eye tracking study. We propose that human users are more attracted by multi-perspective images, which emphasise the “semantic foci” of the scene, than by those being synthesized statically with only one geometrical prospect.