Paul Zikas

Manos Kamarianakis, Antonis Protopsaltis, Dimitris Angelis et al.

This work presents the introduction of UniSG^GA, a novel integrated scenegraph structure, that to incorporates behavior and geometry data on a 3D scene. It is specifically designed to seamlessly integrate Graph Neural Networks (GNNs) and address the challenges associated with transforming a 3D scenegraph (3D-SG) during generative tasks. To effectively capture and preserve the topological relationships between objects in a simplified way, within the graph representation, we propose UniSG^GA, that seamlessly integrates Geometric Algebra (GA) forms. This novel approach enhances the overall performance and capability of GNNs in handling generative and predictive tasks, opening up new possibilities and aiming to lay the foundation for further exploration and development of graph-based generative AI models that can effectively incorporate behavior data for enhanced scene generation and synthesis.

Manos Kamarianakis, Nick Lydatakis, Antonis Protopsaltis et al.

In this work, we present an integrated geometric framework: "deep- cut" that enables for the first time a user to geometrically and algorithmically cut, tear and drill the surface of a skinned model without prior constraints, layered on top of a custom soft body mesh deformation algorithm. Both layered algorithms in this frame- work yield real-time results and are amenable for mobile Virtual Reality, in order to be utilized in a variety of interactive application scenarios. Our framework dramatically improves real-time user experience and task performance in VR, without pre-calculated or artificially designed cuts, tears, drills or surface deformations via predefined rigged animations, which is the current state-of-the-art in mobile VR. Thus our framework improves user experience on one hand, on the other hand saves both time and costs from expensive, manual, labour-intensive design pre-calculation stages.

George Papagiannakis, Paul Zikas, Nick Lydatakis et al.

In this work, we present MAGES 3.0, a novel Virtual Reality (VR)-based authoring SDK platform for accelerated surgical training and assessment. The MAGES Software Development Kit (SDK) allows code-free prototyping of any VR psychomotor simulation of medical operations by medical professionals, who urgently need a tool to solve the issue of outdated medical training. Our platform encapsulates the following novel algorithmic techniques: a) collaborative networking layer with Geometric Algebra (GA) interpolation engine b) supervised machine learning analytics module for real-time recommendations and user profiling c) GA deformable cutting and tearing algorithm d) on-the-go configurable soft body simulation for deformable surfaces.

Stéphanie Bertrand, Martha Vassiliadi, Paul Zikas et al.

This chapter will extend its preliminary scope by examining how literary transportation further amplifies presence and affects user response vis-á-vis virtual heritage by focusing on embodiment and aesthetic experience. To do so, it will draw on recent findings emerging from the fields of applied psychology, neuroaesthetics and cognitive literary studies; and consider a case study advancing the use of literary travel narratives in the design of DCH applications for Antiquities - in this case the well-known ancient Greek monument of Acropolis. Subsequently, the chapter will discuss how Literary-based MR Presence shifts public reception from an education-entertainment-touristic consumption paradigm to a response predicated on valuation. It will show that this type of public engagement is more closely aligned both with MR applications' default mode of usership, and with newly emerging conceptions of a user-centered museum (e.g., the Museum 3.0), thus providing a Virtual Museum model expressly suited to cultural heritage.

Efstratios Geronikolakis, Paul Zikas, Steve Kateros et al.

In this work, a new and innovative way of spatial computing that appeared recently in the bibliography called True Augmented Reality (AR), is employed in cultural heritage preservation. This innovation could be adapted by the Virtual Museums of the future to enhance the quality of experience. It emphasises, the fact that a visitor will not be able to tell, at a first glance, if the artefact that he/she is looking at is real or not and it is expected to draw the visitors' interest. True AR is not limited to artefacts but extends even to buildings or life-sized character simulations of statues. It provides the best visual quality possible so that the users will not be able to tell the real objects from the augmented ones. Such applications can be beneficial for future museums, as with True AR, 3D models of various exhibits, monuments, statues, characters and buildings can be reconstructed and presented to the visitors in a realistic and innovative way. We also propose our Virtual Reality Sample application, a True AR playground featuring basic components and tools for generating interactive Virtual Museum applications, alongside a 3D reconstructed character (the priest of Asinou church) facilitating the storyteller of the augmented experience.

Paul Zikas, George Papagiannakis, Nick Lydatakis et al.

Virtual reality (VR) has re-emerged as a low-cost, highly accessible consumer product, and training on simulators is rapidly becoming standard in many industrial sectors. However, the available systems are either focusing on gaming context, featuring limited capabilities or they support only content creation of virtual environments without any rapid prototyping and modification. In this project, we propose a code-free, visual scripting platform to replicate gamified training scenarios through rapid prototyping and VR software design patterns. We implemented and compared two authoring tools: a) visual scripting and b) VR editor for the rapid reconstruction of VR training scenarios. Our visual scripting module is capable to generate training applications utilizing a node-based scripting system whereas the VR editor gives user/developer the ability to customize and populate new VR training scenarios directly from the virtual environment. We also introduce action prototypes, a new software design pattern suitable to replicate behavioral tasks for VR experiences. In addition, we present the training scenegraph architecture as the main model to represent training scenarios on a modular, dynamic and highly adaptive acyclic graph based on a structured educational curriculum. Finally, a user-based evaluation of the proposed solution indicated that users - regardless of their programming expertise - can effectively use the tools to create and modify training scenarios in VR.