Alternate Reality Games: Gamification for Performance
While formal training and communication are a foundational approach to developing employees in the workplace, alternate reality games (ARGs) provide a framework for increased and sustained engagement within business organizations. ARGs are transmedia experiences designed to generate engagement and immersive learning beyond what is achieved in formal and conventional training and communication approaches. Alternate Reality Games: Gamification for Performance leads you through the fundamentals of ARGs. It includes a discussion of what is and is not an ARG, citing examples and identifying business challenges that can be addressed through ARGs. It presents case studies that illustrate the variety of forms that ARGs take and the issues to which they can be applied, such as improving performance and critical communication situations. It also gives guidelines for creating your own ARGs, reviewing the process and technological tools and considerations relevant to their creation. Presenting a thorough examination of the beneficial roles ARGs can play in the business environment as well as methods for creating effective ARGs, Alternate Reality Games: Gamification for Performance is an ideal reference for those approaching or considering ARGs for the first time as well as the training professional or professional game designer. It presents a comprehensive overview of the advantages of applying ARGs to the workplace as well as methods for designing and using them.
About the Author
Charles Palmer, Harrisburg University of Science and Technology, Pennsylvania, USA Andy Petroski, Harrisburg University of Science and Technology, Pennsylvania, USA.
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A timely book containing foundations and current research directions on emotion recognition by facial expression, voice, gesture and biopotential signals This book provides a comprehensive examination of the research methodology of different modalities of emotion recognition. Key topics of discussion include facial expression, voice and biopotential signal-based emotion recognition. Special emphasis is given to feature selection, feature reduction, classifier design and multi-modal fusion to improve performance of emotion-classifiers. Written by several experts, the book includes several tools and techniques, including dynamic Bayesian networks, neural nets, hidden Markov model, rough sets, type-2 fuzzy sets, support vector machines and their applications in emotion recognition by different modalities. The book ends with a discussion on emotion recognition in automotive fields to determine stress and anger of the drivers, responsible for degradation of their performance and driving-ability. There is an increasing demand of emotion recognition in diverse fields, including psycho-therapy, bio-medicine and security in government, public and private agencies. The importance of emotion recognition has been given priority by industries including Hewlett Packard in the design and development of the next generation human-computer interface (HCI) systems. Emotion Recognition: A Pattern Analysis Approach would be of great interest to researchers, graduate students and practitioners, as the book * Offers both foundations and advances on emotion recognition in a single volume * Provides a thorough and insightful introduction to the subject by utilizing computational tools of diverse domains * Inspires young researchers to prepare themselves for their own research * Demonstrates direction of future research through new technologies, such as Microsoft Kinect, EEG systems etc.
About the Author
Amit Konar is a Professor of Electronics and Tele-Communication Engineering, Jadavpur University, India, where he offers graduate-level courses on Artificial Intelligence and directs research in Cognitive Science, Robotics and Human-Computer Interfaces. Dr. Konar is the recipient of many prestigious grants and awards and is an author of 10 books and over 350 research publications. He offered consultancy services to Government and private industries. He served editorial services to many journals, including IEEE Transactions on Systems, Man and Cybernetics (Part-A) and IEEE Transactions on Fuzzy Systems.
Aruna Chakraborty is an Associate Professor with the Department of Computer Science and Engineering, St. Thomas’ College of Engineering and Technology, India. She is also a Visiting Faculty with Jadavpur University, where she offers graduate-level courses on Intelligent Automation and Robotics, and Cognitive Science. Her research interest includes human-computer interfaces, emotional intelligence and reasoning with fuzzy logic.
While the earliest character representations in video games were rudimentary in terms of their presentation and performance, the virtual characters that appear in games today can be extremely complex and lifelike. These are characters that have the potential to make a powerful and emotional connection with gamers. As virtual characters become more intricate and varied, there is a growing need to examine the theory and practice of virtual character design. This book seeks to develop a series of critical frameworks to support the analysis and design of virtual characters. Virtual Character Design for Games and Interactive Media covers a breadth of topics to establish a relationship between pertinent artistic and scientific theories and good character design practice. Targeted at students, researchers, and professionals, the book aims to show how both character presentation and character performance can be enhanced through careful consideration of underlying theory. The book begins with a focus on virtual character presentation, underpinned by a discussion of biological, artistic, and sociological principles. Next it looks at the performance of virtual characters, encompassing the psychology of emotion and personality, narrative and game design theories, animation, and acting. The book concludes with a series of applied virtual character design examples. These examples examine the aesthetics of player characters, the design and performance of the wider cast of game characters, and the performance of characters within complex, hyperreal worlds.
About the Author
Dr. Robin J.S. Sloan is a lecturer at Abertay University in Dundee, Scotland. Robin attained a first degree in computer arts and worked in the Scottish games industry before researching for a PhD in character animation. His doctoral research focused on the development of emotional animation for interactive characters, with emphasis on both the psychological principles of facial expressions and the creative principles of animated performance. Robin currently teaches Game Art and Game Design to students studying for degrees within the School of Arts, Media and Computer Games, which houses the UK’s first Centre for Excellence in Computer Games Education. Besides character design, his research interests include game-design processes, games nostalgia and culture, and games education.
New media — we are told — exist at the bleeding edge of obsolescence. We thus forever try to catch up, updating to remain the same. Meanwhile, analytic, creative, and commercial efforts focus exclusively on the next big thing: figuring out what will spread and who will spread it the fastest. But what do we miss in this constant push to the future? In Updating to Remain the Same, Wendy Hui Kyong Chun suggests another approach, arguing that our media matter most when they seem not to matter at all — when they have moved from “new” to habitual. Smart phones, for example, no longer amaze, but they increasingly structure and monitor our lives. Through habits, Chun says, new media become embedded in our lives — indeed, we become our machines: we stream, update, capture, upload, link, save, trash, and troll. Chun links habits to the rise of networks as the defining concept of our era. Networks have been central to the emergence of neoliberalism, replacing “society” with groupings of individuals and connectable “YOUS.” (For isn’t “new media” actually “NYOU media”?) Habit is central to the inversion of privacy and publicity that drives neoliberalism and networks. Why do we view our networked devices as “personal” when they are so chatty and promiscuous? What would happen, Chun asks, if, rather than pushing for privacy that is no privacy, we demanded public rights — the right to be exposed, to take risks and to be in public and not be attacked?
About the Author
Wendy Hui Kyong Chun, who has studied both systems design and English literature, is Professor of Modern Culture and Media at Brown University. She is the author of Control and Freedom: Power and Paranoia in the Age of Fiber Optics and Programmed Visions: Software and Memory, both published by the MIT Press.
Presents methodologies for modeling, analysis and recognition of shapes of facial surfaces, from fundamental ideas in geometry and shape analysis, to cutting-edge applications This text presents methodologies for analyzing shapes of facial surfaces, develops computational tools for analyzing 3D face data, and illustrates them using state-of-the-art applications. The methodologies chosen are based on efficient representations, metrics, comparisons, and classifications of features that are especially relevant in the context of 3D measurements of human faces. These frameworks have a long-term utility in face analysis, taking into account the anticipated improvements in data collection, data storage, processing speeds, and application scenarios expected as the discipline develops further. Covers a wide range of applications including biometrics, 3D animation, facial surgery, forensics, and video communications. Contains numerous exercises and algorithms. Covers the fundamentals and methodologies of 3D face analysis Includes a section specifically on applications, making the book of interest to both those in research and industry. Brings together information currently available in disparate sources in a much-needed comprehensive textbook. All methods are tested on FRGC or subsets of FRGC datasets, allowing a comparison on a single dataset A companion website hosts updates, information on relevant databases, and demonstrations.
About the Author
Mohamed Daoudi, TELECOM Lille 1, France Professor Daoudi is a member of the computer science department at TELECOM Lille 1, and a member of the IEEE. Prof. Daoudi is an editor of the Journal of Multimedia and has been a guest co-editor of the Annals of Telecommunications for a special issue on Technologies and Tools for 3D Imaging. He co-edited 3D Object Processing: Compression, Indexing and Watermarking published by Wiley in 2008. Anuj Srivastava, Florida State University, USA Professor Srivastava is a member of the department of statistics at Florida State University, and a member of the IEEE and ASA. He has been an associate editor of the Journal of Statistical Planning and Interference, IEEE Transactions on Signal Processing, and IEEE Transactions on Pattern Analysis and Machine Intelligence, which he also edited a special issue of on Shape Modeling. He has published over 30 journal papers and 7 book chapters in edited volumes. Remco Veltkamp, Universiteit Utrecht, The Netherlands Professor Veltkamp is a member of the department of Information and Computing Sciences at Utrecht University, focusing on multimedia applications. He is an editor of Pattern Recognition Journal and the International Journal on Shape Modeling. He has also guest edited several journals including a special issue on Multimedia Algorithmics in Multimedia Tools and Applications, and a special issue on Shape Reasoning and Understanding in Computers & Graphics. Prof. Veltkamp has published 30 journal papers, 13 book chapters in edited volumes, co-edited several conference proceedings and has co-edited State-of-the-art in Content-based Image and Video Retrieval published by Springer in 2001.