This book provides a deep understanding of state-of-art methods for simulation of heterogeneous crowds in computer graphics. It will cover different aspects that are necessary to achieve plausible crowd behaviors. The book will be a review of the most recent literature in this field that can help professionals and graduate students interested in this field to get up to date with the latest contributions, and open problems for their possible future research. The chapter contributors are well known researchers and practitioners in the field and they include their latest contributions in the different topics required to achieve believable heterogeneous crowd simulation.

This book describes, from a computer science viewpoint the software, methods of simulating and analysing crowds with a particular focus on the effects of panic in emergency situations. The power of modern technology impacts on modern life in multiple ways every day. A variety of scientific models and computational tools have been developed to improve human safety and comfort in built environments. In particular, understanding pedestrian behaviours during egress situations is of considerable importance in such contexts. Moreover, some places are built for large numbers of people (such as train stations and airports and high volume special activities such as sporting events). Simulating Crowds in Egress Scenarios discusses the use of computational crowd simulation to reproduce and evaluate egress performance in specific scenarios. Several case studies are included, evaluating the work and different analyses, and comparisons of simulation data versus data obtained from real-life experiments are given.

This volume describes frontiers in social-behavioral modeling for contexts as diverse as national security, health, and on-line social gaming. Recent scientific and technological advances have created exciting opportunities for such improvements. However, the book also identifies crucial scientific, ethical, and cultural challenges to be met if social-behavioral modeling is to achieve its potential. Doing so will require new methods, data sources, and technology. The volume discusses these, including those needed to achieve and maintain high standards of ethics and privacy. The result should be a new generation of modeling that will advance science and, separately, aid decision-making on major social and security-related subjects despite the myriad uncertainties and complexities of social phenomena. Intended to be relatively comprehensive in scope, the volume balances theory-driven, data-driven, and hybrid approaches. The latter may be rapidly iterative, as when artificial-intelligence methods are coupled with theory-driven insights to build models that are sound, comprehensible and usable in new situations. With the intent of being a milestone document that sketches a research agenda for the next decade, the volume draws on the wisdom, ideas and suggestions of many noted researchers who draw in turn from anthropology, communications, complexity science, computer science, defense planning, economics, engineering, health systems, medicine, neuroscience, physics, political science, psychology, public policy and sociology. In brief, the volume discusses: Cutting-edge challenges and opportunities in modeling for social and behavioral science Special requirements for achieving high standards of privacy and ethics New approaches for developing theory while exploiting both empirical and computational data Issues of reproducibility, communication, explanation, and validation Special requirements for models intended to inform decision making about complex social systems

The growth of a global digital economy has enabled rapid communication, instantaneous movement of funds, and availability of vast amounts of information. With this come challenges such as the vulnerability of digitalized sociotechnological systems (STSs) to destructive events (earthquakes, disease events, terrorist attacks). Similar issues arise for disruptions to complex linked natural and social systems (from changing climates, evolving urban environments, etc.). This book explores new approaches to the resilience of sociotechnological and natural-social systems in a digital world of big data, extraordinary computing capacity, and rapidly developing methods of Artificial Intelligence. Most of the book’s papers were presented at the Workshop on Big Data and Systems Analysis held at the International Institute for Applied Systems Analysis in Laxenburg, Austria in February, 2020. Their authors are associated with the Task Group “Advanced mathematical tools for data-driven applied systems analysis” created and sponsored by CODATA in November, 2018. The world-wide COVID-19 pandemic illustrates the vulnerability of our healthcare systems, supply chains, and social infrastructure, and confronts our notions of what makes a system resilient. We have found that use of AI tools can lead to problems when unexpected events occur. On the other hand, the vast amounts of data available from sensors, satellite images, social media, etc. can also be used to make modern systems more resilient. Papers in the book explore disruptions of complex networks and algorithms that minimize departure from a previous state after a disruption; introduce a multigrammatical framework for the technological and resource bases of today’s large-scale industrial systems and the transformations resulting from disruptive events; and explain how robotics can enhance pre-emptive measures or post-disaster responses to increase resiliency. Other papers explore current directions in data processing and handling and principles of FAIRness in data; how the availability of large amounts of data can aid in the development of resilient STSs and challenges to overcome in doing so. The book also addresses interactions between humans and built environments, focusing on how AI can inform today’s smart and connected buildings and make them resilient, and how AI tools can increase resilience to misinformation and its dissemination.

This book constitutes the refereed proceedings of the 36th Computer Graphics International Conference, CGI 2019, held in Calgary, AB, Canada, in June 2019. The 30 revised full papers presented together with 28 short papers were carefully reviewed and selected from 231 submissions. The papers address topics such as: 3D reconstruction and rendering, virtual reality and augmented reality, computer animation, geometric modelling, geometric computing, shape and surface modelling, visual analytics, image processing, pattern recognition, motion planning, gait and activity biometric recognition, machine learning for graphics and applications in security, smart electronics, autonomous navigation systems, robotics, geographical information systems, and medicine and art.

This book constitutes the refereed proceedings of the 12th International Conference on e-Learning and Games, EDUTAINMENT 2018, held in Xi’an, China, in June 2018. The 32 full and 32 short papers presented in this volume were carefully reviewed and selected from 85 submissions. The papers were organized in topical sections named: virtual reality and augmented reality in edutainment; gamification for serious game and training; graphics, imaging and applications; game rendering and animation; game rendering and animation and computer vision in edutainment; e-learning and game; and computer vision in edutainment.

The book includes the contributions to the international conference “18th 3D GeoInfo”. The papers published in the book were selected through a double-blind review process. 3D GeoInfo has been the forum joining researchers, professionals, software developers, and data providers designing and developing innovative concepts, tools, and application related to 3D geo data processing, modeling, management, analytics, and simulation. A big focus is on topics related to data modeling for 3D city and landscape models as well as their many and diverse applications. This conference series is very successfully running since 2006 and has been hosted by countries in Europe, Asia, Africa, North America, and Australia. In the period 2006 to 2017, the proceedings has been published by Springer in this series with Thomas H. Kolbe being the editor of the 2010 edition of the conference proceedings. 18th 3DGeoInfo was organized by Technical University of Munich in cooperation with the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF), the local associations Runder Tisch GIS e.V. (Round Table GIS) and Leonhard Obermeyer Center—TUM Center of Digital Methods for the Built Environment, and the City of Munich. The international program committee consisted of committee members of previous 3D GeoInfo conferences and further leading scientists in the field of 3D Geoinformation Science.

High-performance computing (HPC) describes the use of connected computing units to perform complex tasks. It relies on parallelization techniques and algorithms to synchronize these disparate units in order to perform faster than a single processor could, alone. Used in industries from medicine and research to military and higher education, this method of computing allows for users to complete complex data-intensive tasks. This field has undergone many changes over the past decade, and will continue to grow in popularity in the coming years. Innovative Research Applications in Next-Generation High Performance Computing aims to address the future challenges, advances, and applications of HPC and related technologies. As the need for such processors increases, so does the importance of developing new ways to optimize the performance of these supercomputers. This timely publication provides comprehensive information for researchers, students in ICT, program developers, military and government organizations, and business professionals.

This practically-focused book presents a computational model for detection and analysis of pedestrian features in crowds from video sequences. The study of human behavior is a subject of great scientific interest and probably an inexhaustible source of research. The analysis of pedestrians and groups in crowds is relevant in several areas of application, such as security, entertainment, environmental and public spaces planning and social sciences. Cultural and personality aspects are attributes that can influence personal behavior and affect the group in which individuals belong. In this sense, we consider different ways of characterizing individuals and groups in crowds with respect to their relationship with the geometrical space and time. We discuss and describe an approach to extract and analyse, from the Computer Science point of view, emotions, personalities and cultural aspects from crowds and groups of pedestrians, using Computer Vision techniques. Extracting characteristics from real pedestrians and crowds, benefits other areas, such as: architecture and design (planning spaces to maximize pedestrian and group-environment fit); security and surveillance (design of evacuation plans considering characteristics of the crowds and detection of abnormal events); entertainment (more realistic crowds in movies and games reproducing characteristics from real pedestrians and crowds); social sciences (understanding of human behavior), among others. A big challenge in this area of research is the comparison with real life data. In this book, we successfully compared the results of the proposed approach with Psychology literature, where several studies aimed to analysis human behavior.