Identifying key factors to distinguish artificial and human avatars in the metaverse: insights from software professionals

The Metaverse comprises a network of interconnected 3D virtual worlds, poised to become the primary gateway for future online experiences. These experiences hinge upon the use of avatars, participants' virtual counterparts capable of exhibiting human-like non-verbal behaviors, such as gestures, walking, dancing, and social interaction. Discerning between human and artificial avatars becomes crucial as the concept gains prominence. Advances in artificial intelligence have facilitated the creation of virtual human-like entities, underscoring the importance of distinguishing between virtual agents and human characters. This paper investigates the factors differentiating human and virtual participants within the Metaverse environment. A semi-structured interview approach was employed, with data collected from software practitioners (N=10). Our preliminary findings indicate that response speed, adaptability to unforeseen events, and recurring scenarios play significant roles in determining whether an entity in the virtual world is a human or an intelligent agent

Digital anthropology

The textbook supplements the lecture material with topical issues of the philosophy of neural technologies. The material belongs to the section "Philosophy of natural science and technology" of the lecture course on the philosophy and methodology of science. The natural-science aspects of human conscious-ness and technological trends in the evolution of convergent structures of digital ecosystems are described. The evolution of system computer engineering is analyzed

The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions

The Metaverse offers a second world beyond reality, where boundaries are non-existent, and possibilities are endless through engagement and immersive experiences using the virtual reality (VR) technology. Many disciplines can benefit from the advancement of the Metaverse when accurately developed, including the fields of technology, gaming, education, art, and culture. Nevertheless, developing the Metaverse environment to its full potential is an ambiguous task that needs proper guidance and directions. Existing surveys on the Metaverse focus only on a specific aspect and discipline of the Metaverse and lack a holistic view of the entire process. To this end, a more holistic, multi-disciplinary, in-depth, and academic and industry-oriented review is required to provide a thorough study of the Metaverse development pipeline. To address these issues, we present in this survey a novel multi-layered pipeline ecosystem composed of (1) the Metaverse computing, networking, communications and hardware infrastructure, (2) environment digitization, and (3) user interactions. For every layer, we discuss the components that detail the steps of its development. Also, for each of these components, we examine the impact of a set of enabling technologies and empowering domains (e.g., Artificial Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on its advancement. In addition, we explain the importance of these technologies to support decentralization, interoperability, user experiences, interactions, and monetization. Our presented study highlights the existing challenges for each component, followed by research directions and potential solutions. To the best of our knowledge, this survey is the most comprehensive and allows users, scholars, and entrepreneurs to get an in-depth understanding of the Metaverse ecosystem to find their opportunities and potentials for contribution

LEARNING TO RIG CHARACTERS

With the emergence of 3D virtual worlds, 3D social media, and massive online games, the need for diverse, high-quality, animation-ready characters and avatars is greater than ever. To animate characters, artists hand-craft articulation structures, such as animation skeletons and part deformers, which require significant amount of manual and laborious interaction with 2D/3D modeling interfaces. This thesis presents deep learning methods that are able to significantly automate the process of character rigging. First, the thesis introduces RigNet, a method capable of predicting an animation skeleton for an input static 3D shape in the form of a polygon mesh. The predicted skeletons match the animator expectations in joint placement and topology. RigNet also estimates surface skin weights which determine how the mesh is animated given the different skeletal poses. In contrast to prior work that fits pre-defined skeletal templates with hand-tuned objectives, RigNet is able to automatically rig diverse characters, such as humanoids, quadrupeds, toys, birds, with varying articulation structure and geometry. RigNet is based on a deep neural architecture that directly operates on the mesh representation. The architecture is trained on a diverse dataset of rigged models that we mined online and curated. The dataset includes 2.7K polygon meshes, along with their associated skeletons and corresponding skin weights. Second, the thesis introduces Morig, a method that automatically rigs character meshes driven by single-view point cloud streams capturing the motion of performing characters. Compared to RigNet, MoRig\u27s rigging is \emph{motion-aware}: its neural network encodes motion cues from the point clouds into compact feature representations that are informative about the articulated parts of the performing character. These motion-aware features guide the inference of an appropriate skeletal rig for the input mesh. Furthermore, Morig is able to animate the rig according to the captured point cloud motion. Morig can handle diverse characters with different morphologies (e.g., humanoids, quadrupeds, toy characters). It also accounts for occluded regions in the point clouds and mismatches in the part proportions between the input mesh and captured character. Third, the thesis introduces APES, a method that takes as input 2D raster images depicting a small set of poses of a character shown in a sprite sheet, and identifies articulated parts useful for rigging the character. APES uses a combination of neural network inference and integer linear programming to identify a compact set of articulated body parts, e.g. head, torso and limbs, that best reconstruct the input poses. Compared to Morig and RigNet that require a large collection of training models with associated skeletons and skinning weights, APES\u27 neural architecture relies on less effortful supervision from (i) pixel correspondences readily available in existing large cartoon image datasets (e.g., Creative Flow), (ii) a relatively small dataset of 57 cartoon characters segmented into moving parts. Finally, the thesis discusses future research directions related to combining neural rigging with 3D and 4D reconstruction of characters from point cloud data and 2D video as well as automating the process of motion synthesis for 3D characters

Proceedings of the Conference on Production Systems and Logistics: CPSL 2022

[no abstract available

The legal regime for anti-cyberlaundering

Doctor Legum - LLDAlong with its inumerable wonders, the advent of the internet has brought with it very bad vices. The notion of convenience, which comes with the use of the internet, can be attributed to criminals who wish to disguise the proceeds of their ill-derived funds, or what is better known as cyberlaundering. Cyberlaundering is a phenomenon that seems negligible on face value, but, to the contrary, has very dire effects, especially on national economies, which are in no way trifling.This study describes the problem of cyberlaundering, pointing out the various legal issues pertaining to it. Given that cyberlaundering is a comparatively new crime, which is not yet conceptualized legally, criminal justice authorities find it hard to detect, investigate and prosecute cyberlaundering. An adequate legal regime against cyberlaundering is currently non-existent, as there is presently no concise international or national legal framework in place to contain the problem. Whilst the chief focus of the thesis is to devise a legal framework to combat cyberlaundering, considerable attention is also devoted to the tension that arises between public and private interests, amongst several other legal issues that come to play along the way. This is a debate that necessarily arises when legislatures resort to more radical anti-cyberlaundering laws. The study advocates a middle ground, which leads to the desired end of curbing the exponential growth of cyberlaundering, at the very least

Электронные системы и технологии

В сборнике опубликованы материалы докладов, представленных на 58-й НК аспирантов, магистрантов и студентов БГУИР, по направлению «Электронные системы и технологии». Авторами рассматриваются вопросы имитационного моделирования, численных методов, новых информационных технологий в образовании, радиоэлектронике, телекоммуникациях, вычислительных сетях, а также возможности современных систем автоматизированного проектирования. Материалы одобрены оргкомитетом и публикуются с учетом того, что авторская позиция и стилистические особенности публикаций полностью сохранены при соблюдении требований к оформлению материалов. Сборник предназначен для широкого круга специалистов в области электронных систем и технологий. Представленные материалы будет полезны научным и инженерно-техническим работникам, преподавателям, аспирантам, магистрантам и студентам технических вузов. Сборник индексируется в РИНЦ

UNSUPERVISED CONVERSION OF 3D MODELS FOR INTERACTIVE METAVERSES

A virtual-world environment becomes a truly engaging platform when users have the ability to insert 3D content into the world. However, arbitrary 3D content is often not optimized for real-time rendering, limiting the ability of clients to display large scenes consisting of hundreds or thousands of objects. We present the design and implementation of an automatic, unsupervised conversion process that transforms 3D content into a format suitable for real-time rendering while minimizing loss of quality. The resulting progressive format includes a base mesh, allowing clients to quickly display the model, and a progressive portion for streaming additional detail as desired. Sirikata, an open virtual world platform, has processed over 700 models using this method