Browsing by Author "Aristidou, Andreas"

Now showing 1 - 4 of 4
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    Collaborative VR: Solving Riddles in the Concept of Escape Rooms
    (The Eurographics Association, 2023) Ioannou, Afxentis; Lemonari, Marilena; Liarokapis, Fotis; Aristidou, Andreas; Pelechano, Nuria; Liarokapis, Fotis; Rohmer, Damien; Asadipour, Ali
    The recent state of VR technology enables users to have quick and easy access to multiple VR functionalities, prompting researchers to explore various aspects of user experiences in virtual environments. In this work, we study alternative means of user communication in collaborative virtual environments (CVEs). We are especially interested in how users manage to convey messages to each other while not being able to see, hear, or text one another. We aim to understand how users choose to utilize the tools provided to them in virtual environments and report their feedback i.e., how this affects engagement level, performance, etc. The objective of our work is to be able to determine the effects of integrating alternative means of communication in users' experience in VR; to examine this, we choose a case study of a collaborative VR escape room. We carry out a user study to evaluate our hypotheses on the effects of nontraditional communication means when performing computer-supported cooperative work (CSCW). We find that players manage to complete their tasks similarly to real-life scenarios, even when not allowing for traditional ways of interpersonal interactions. Through our user survey, we also conclude that it is worth integrating this communication option in other applications as well, which poses further questions as to what is the full potential of incorporating several alternative functionalities that people subtly use in real-life, in VR.
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    Pose Representations for Deep Skeletal Animation
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Andreou, Nefeli; Aristidou, Andreas; Chrysanthou, Yiorgos; Dominik L. Michels; Soeren Pirk
    Data-driven skeletal animation relies on the existence of a suitable learning scheme, which can capture the rich context of motion. However, commonly used motion representations often fail to accurately encode the full articulation of motion, or present artifacts. In this work, we address the fundamental problem of finding a robust pose representation for motion, suitable for deep skeletal animation, one that can better constrain poses and faithfully capture nuances correlated with skeletal characteristics. Our representation is based on dual quaternions, the mathematical abstractions with well-defined operations, which simultaneously encode rotational and positional orientation, enabling a rich encoding, centered around the root. We demonstrate that our representation overcomes common motion artifacts, and assess its performance compared to other popular representations. We conduct an ablation study to evaluate the impact of various losses that can be incorporated during learning. Leveraging the fact that our representation implicitly encodes skeletal motion attributes, we train a network on a dataset comprising of skeletons with different proportions, without the need to retarget them first to a universal skeleton, which causes subtle motion elements to be missed. Qualitative results demonstrate the usefulness of the parameterization in skeleton-specific synthesis.
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    Safeguarding our Dance Cultural Heritage
    (The Eurographics Association, 2022) Aristidou, Andreas; Chalmers, Alan; Chrysanthou, Yiorgos; Loscos, Celine; Multon, Franck; Parkins, J. E.; Sarupuri, Bhuvan; Stavrakis, Efstathios; Hahmann, Stefanie; Patow, Gustavo A.
    Folk dancing is a key aspect of intangible cultural heritage that often reflects the socio-cultural and political influences prevailing in different periods and nations; each dance produces a meaning, a story with the help of music, costumes and dance moves. It has been transmitted from generation to generation, and to different countries, mainly due to movements of people carrying and disseminating their civilization. However, folk dancing, amongst other intangible heritage, is at high risk of disappearing due to wars, the moving of populations, economic crises, modernization, but most importantly, because these fragile creations have been modified over time through the process of collective recreation, and/or changes in the way of life. In this tutorial, we show how the European Project, SCHEDAR, exploited emerging technologies to digitize, analyze, and holistically document our intangible heritage creations, that is a critical necessity for the preservation and the continuity of our identity as Europeans.
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    Virtual Dance Museum: the Case of Greek/Cypriot Folk Dancing
    (The Eurographics Association, 2021) Aristidou, Andreas; Andreou, Nefeli; Charalambous, Loukas; Yiannakidis, Anastasios; Chrysanthou, Yiorgos; Hulusic, Vedad and Chalmers, Alan
    In this paper, we have designed and developed a virtual dance museum to provide the technological tools that allow for widely educating the public, most specifically the youngest generations, about the story, costumes, music, and history of our dances. The holistic documentation of our intangible cultural heritage creations is a critical necessity for the preservation and the continuity of our identity as Europeans. In that direction, we have employed a specially designed relational database schema that holistically structures the information within the database, and is ideal for archiving, presenting, further analyzing, and re-using dance motion data. Data have been retargeted to a virtual character, dressed with traditional uniform and simulated to achieve realism. The users can view and interact with the archived data using advanced 3D character visualization in three ways: via an online 3D virtual environment; in virtual reality using headset; and in augmented reality, where the 3D characters can co-inhabit the real world. Our museum is publicly accessible, and also enables motion data reusability, facilitating dance learning applications through gamification.