Theodoros Kyriakou

The evolving landscape of performing arts, driven by advancements in Extended Reality (XR) and the Metaverse, presents transformative opportunities for digitizing musical experiences. This comprehensive survey explores the relatively unexplored field of Virtual Instrument Performances (VIP), addressing challenges related to motion capture precision, multi-modal interactions, and the integration of sensory modalities, with a focus on fostering inclusivity, creativity, and live performances in diverse settings.

We present P2C, a method for simulating realistic and diverse crowds by parameterizing reference crowd data. This approach enables fine-grained control, allowing artists to modify intuitive behavior parameters in localized regions during runtime, facilitating the creation of customizable agent behaviors and interactions in crowd simulations. The method integrates four fundamental behaviors into an existing Reinforcement Learning-based system and demonstrates its potential through predictive power evaluation on real data, comparing favorably against existing baselines.

Diversity among agents' behaviors and heterogeneity in virtual crowds in general, is an important aspect of crowd simulation as it is crucial to the perceived realism and plausibility of the resulting simulations. Heterogeneous crowds constitute the pillar in creating numerous real-life ... scenarios such as museum exhibitions, which require variety in agent behaviors, from basic collision avoidance to more complex interactions both among agents and with environmental features. Most of the existing systems optimize for specific behaviors such as goal seeking, and neglect to take into account other behaviors and how these interact together to form diverse agent profiles. In this paper, we present a RL-based framework for learning multiple agent behaviors concurrently. We optimize the agent by varying the importance of the selected behaviors (goal seeking, collision avoidance, interaction with environment, and grouping) while training; essentially we have a reward function that changes dynamically during training. The importance of each separate sub-behavior is added as input to the policy, resulting in the development of a single model capable of capturing as well as enabling dynamic run-time manipulation of agent profiles; thus allowing configurable profiles. Through a series of experiments, we verify that our system provides users with the ability to design virtual scenes; control and mix agent behaviors thus creating personality profiles, and assign different profiles to groups of agents. Moreover, we demonstrate that interestingly the proposed model generalizes to situations not seen in the training data such as a) crowds with higher density, b) behavior weights that are outside the training intervals and c) to scenes with more intricate environment layouts.

The project «PREMIERE» (Performing arts in a new era: AI and XR tools for better understanding, preservation, enjoyment and accessibility) seeks to modernize the performing arts focusing on dance and theater by using advanced digital technologies to support the whole lifecycle of performances. The overall objective of PREMIERE is to develop and validate a comprehensive ecosystem of digital applications, powered by leading edge AI, XR and 3D technologies, designed to fulfill the needs of diverse end-user communities involved in the main stages of the lifecycle of performing arts productions.

ReInHerit is an Horizon2020 project that aspires to disrupt the current status quo of communication, collaboration and innovation exchange between museums and cultural heritage sites, in a sense that it will connect cultural heritage collections and sites, and present Europe’s tangible and intangible heritage to citizens and tourists in their wider historical and geographical contexts. The ReInHerit project is proposing a very innovative model of sustainable heritage management, through which a dynamic network will be born; this network comprised of cultural heritage professionals, innovation and cultural heritage solution tech experts, researchers, national museums, regional and local museums, and representative managers of Heritage Label sites.