Fotis Liarokapis

HC
h-index35
5papers
69citations
Novelty30%
AI Score34

5 Papers

32.7HCApr 14
Responsible Trauma Research: Designing Effective and Sustainable Virtual Reality Exposure Studies

Annalisa Degenhard, Sophia Ppali, Fotis Liarokapis et al.

Virtual reality exposure therapy (VRET) enables controlled exposure to trauma-related stimuli to facilitate memory access and emotional processing. However, the field remains underexplored for complex post-traumatic stress disorder (C-PTSD). Unlike single-trauma PTSD, C-PTSD requires highly individualized triggers that are difficult to identify and implement safely. We conducted a feasibility study with 11 patients, two trauma therapists, and a VR developer to explore integrating VRET into C-PTSD treatment while safeguarding all stakeholders. Initial findings indicate that simple objects can be just as effective as complex scenes, therapeutic success does not correlate with VR presence levels, and the design process itself became integral to therapy rather than preparatory. However, involving developers in therapy sessions led to considerable emotional stress and role confusion, which required a cautious approach. Based on these insights, we provide methodological recommendations for safe and patient-centered VRET studies that balance therapeutic effectiveness with stakeholder safety across the research process.

CLApr 7, 2025
Bridging Industrial Expertise and XR with LLM-Powered Conversational Agents

Despina Tomkou, George Fatouros, Andreas Andreou et al.

This paper introduces a novel integration of Retrieval-Augmented Generation (RAG) enhanced Large Language Models (LLMs) with Extended Reality (XR) technologies to address knowledge transfer challenges in industrial environments. The proposed system embeds domain-specific industrial knowledge into XR environments through a natural language interface, enabling hands-free, context-aware expert guidance for workers. We present the architecture of the proposed system consisting of an LLM Chat Engine with dynamic tool orchestration and an XR application featuring voice-driven interaction. Performance evaluation of various chunking strategies, embedding models, and vector databases reveals that semantic chunking, balanced embedding models, and efficient vector stores deliver optimal performance for industrial knowledge retrieval. The system's potential is demonstrated through early implementation in multiple industrial use cases, including robotic assembly, smart infrastructure maintenance, and aerospace component servicing. Results indicate potential for enhancing training efficiency, remote assistance capabilities, and operational guidance in alignment with Industry 5.0's human-centric and resilient approach to industrial development.

HCOct 14, 2020
Underwater Augmented Reality for improving the diving experience in submerged archaeological sites

Fabio Bruno, Loris Barbieri, Marino Mangeruga et al.

The Mediterranean Sea has a vast maritime heritage which exploitation is made difficult because of the many limitations imposed by the submerged environment. Archaeological diving tours, in fact, suffer from the impossibility to provide underwater an exhaustive explanation of the submerged remains. Furthermore, low visibility conditions, due to water turbidity and biological colonization, sometimes make very confusing for tourists to find their way around in the underwater archaeological site. To this end, the paper investigates the feasibility and potentials of the underwater Augmented Reality (UWAR) technologies developed in the iMARECulture project for improving the experience of the divers that visit the Underwater Archaeological Park of Baiae (Naples). In particular, the paper presents two UWAR technologies that adopt hybrid tracking techniques to perform an augmented visualization of the actual conditions and of a hypothetical 3D reconstruction of the archaeological remains as appeared in the past. The first one integrates a marker-based tracking with inertial sensors, while the second one adopts a markerless approach that integrates acoustic localization and visual-inertial odometry. The experimentations show that the proposed UWAR technologies could contribute to have a better comprehension of the underwater site and its archaeological remains.

HCOct 13, 2020
An Immersive Virtual Environment for Collaborative Geovisualization

Milan Dolezal, Jiri Chmelik, Fotis Liarokapis

This paper presents an immersive virtual reality environment that can be used to develop collaborative educational applications. Multiple users can collaborate within the virtual shared space and communicate with each other through voice. To asses the feasibility of the collaborative environment a novel case-study concerned the education of a geography was developed and evaluated. The geovisualization experiment scenario explores the possibility of learning geography in a collaborative virtual environment. A user-study with 30 participants was performed. Participants evaluated and commented on the usability and interaction methods used within the virtual environment.

CVOct 11, 2020
Tackling problems of marker-based augmented reality under water

Jan Čejka, Fotis Liarokapis

Underwater sites are a harsh environment for augmented reality applications. Obstacles that must be battled include poor visibility conditions, difficult navigation, and hard manipulation with devices under water. This chapter focuses on the problem of localizing a device under water using markers. It discusses various filters that enhance and improve images recorded under water, and their impact on marker-based tracking. It presents various combinations of 10 image improving algorithms and 4 marker detecting algorithms, and tests their performance in real situations. All solutions are designed to run real-time on mobile devices to provide a solid basis for augmented reality. Usability of this solution is evaluated on locations in Mediterranean Sea. It is shown that image improving algorithms with carefully chosen parameters can reduce the problems with visibility under water and improve the detection of markers. The best results are obtained with marker detecting algorithms that are specifically designed for underwater environments.