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This book discusses the concepts, theory, and core technologies of intelligent theory and human animation, including video based human animation and intelligent technology of motion data management and reusing. It introduces systems developed to demonstrate the technologies of video based animation. Lively pictures and demos throughout the text help make the theory and technologies more accessible to readers.
Introduces systems developed to demonstrate the technologies of video based animation. Lively pictures and demos will be presented to make the theory and technologies more understandable.
This book constitutes the proceedings of the 15th International Conference on Intelligent Virtual Agents, IVA 2015, held in Delft, The Netherlands, in August 2015. The 11 full papers, 22 short papers, and 21 demo and poster papers accepted were carefully reviewed and selected from 70 submissions. Constructing and studying intelligent virtual agents requires knowledge , theories, methods, and tools from a wide range of fields such as computer science, psychology, cognitive sciences, communication, linguistics, interactive media, human-computer interaction, and artificial intelligence. The papers are organized in topical sections such as adaptive dialogue and user modeling; cognitive, affective and social models; nonverbal behavior and gestures; pedagogical agents in health and training; tools and frameworks; turn-taking; virtual agent perception studies.
This edited book explores the many interesting questions that lie at the intersection between AI and HCI. It covers a comprehensive set of perspectives, methods and projects that present the challenges and opportunities that modern AI methods bring to HCI researchers and practitioners. The chapters take a clear departure from traditional HCI methods and leverage data-driven and deep learning methods to tackle HCI problems that were previously challenging or impossible to address. It starts with addressing classic HCI topics, including human behaviour modeling and input, and then dedicates a section to data and tools, two technical pillars of modern AI methods. These chapters exemplify how state-of-the-art deep learning methods infuse new directions and allow researchers to tackle long standing and newly emerging HCI problems alike. Artificial Intelligence for Human Computer Interaction: A Modern Approach concludes with a section on Specific Domains which covers a set of emerging HCI areas where modern AI methods start to show real impact, such as personalized medical, design, and UI automation.
This two volume set of books constitutes the proceedings of the 2014 7th IEEE International Conference Intelligent Systems (IS), or IEEE IS’2014 for short, held on September 24–26, 2014 in Warsaw, Poland. Moreover, it contains some selected papers from the collocated IWIFSGN'2014 ‐ Thirteenth International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets. The conference was organized by theSystems Research Institute, Polish Academy of Sciences, Department IV of Engineering Sciences, Polish Academy of Sciences, and Industrial Institute of Automation and Measurements – PIAP. The papers included in the two proceedings volumes have been subject to a thorough review process by three highly qualified peer reviewers.Comments and suggestions from them have considerable helped improve the quality of the papers but also the division of the volumes into parts, and assignment of the papers to the best suited parts.
The two volume set LNAI 6703 and LNAI 6704 constitutes the thoroughly refereed conference proceedings of the 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, held in Syracuse, NY, USA, in June/July 2011. The total of 92 papers selected for the proceedings were carefully reviewed and selected from 206 submissions. The papers cover a wide number of topics including feature extraction, discretization, clustering, classification, diagnosis, data refinement, neural networks, genetic algorithms, learning classifier systems, Bayesian and probabilistic methods, image processing, robotics, navigation, optimization, scheduling, routing, game theory and agents, cognition, emotion, and beliefs.
Over the last decade, progress in deep learning has had a profound and transformational effect on many complex problems, including speech recognition, machine translation, natural language understanding, and computer vision. As a result, computers can now achieve human-competitive performance in a wide range of perception and recognition tasks. Many of these systems are now available to the programmer via a range of so-called cognitive services. More recently, deep reinforcement learning has achieved ground-breaking success in several complex challenges. This book makes an enormous contribution to this beautiful, vibrant area of study: an area that is developing rapidly both in breadth and depth. Deep learning can cope with a broader range of tasks (and perform those tasks to increasing levels of excellence). This book lays a good foundation for the core concepts and principles of deep learning in gaming and animation, walking you through the fundamental ideas with expert ease. This book progresses in a step-by-step manner. It reinforces theory with a full-fledged pedagogy designed to enhance students' understanding and offer them a practical insight into its applications. Also, some chapters introduce and cover novel ideas about how artificial intelligence (AI), deep learning, and machine learning have changed the world in gaming and animation. It gives us the idea that AI can also be applied in gaming, and there are limited textbooks in this area. This book comprehensively addresses all the aspects of AI and deep learning in gaming. Also, each chapter follows a similar structure so that students, teachers, and industry experts can orientate themselves within the text. There are few books in the field of gaming using AI. Deep Learning in Gaming and Animations teaches you how to apply the power of deep learning to build complex reasoning tasks. After being exposed to the foundations of machine and deep learning, you will use Python to build a bot and then teach it the game's rules. This book also focuses on how different technologies have revolutionized gaming and animation with various illustrations.
This book constitutes the refereed proceedings of the 12th International Conference on Intelligent Virtual Agents, IVA 2012, held in Santa Cruz, CA, USA, in September 2012. The 17 revised full papers presented together with 31 short papers and 18 poster papers were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on IVAs on learning environments; emotion and personality; evaluation and empirical studies; multimodal perception and expression; narrative and interactive applications; social interaction; authoring and tools; conceptual frameworks.
The integration of machine learning techniques and cartoon animation research is fast becoming a hot topic. This book helps readers learn the latest machine learning techniques, including patch alignment framework; spectral clustering, graph cuts, and convex relaxation; ensemble manifold learning; multiple kernel learning; multiview subspace learning; and multiview distance metric learning. It then presents the applications of these modern machine learning techniques in cartoon animation research. With these techniques, users can efficiently utilize the cartoon materials to generate animations in areas such as virtual reality, video games, animation films, and sport simulations
The two-volume proceedings of the ACIIDS 2015 conference, LNAI 9011 + 9012, constitutes the refereed proceedings of the 7th Asian Conference on Intelligent Information and Database Systems, held in Bali, Indonesia, in March 2015. The total of 117 full papers accepted for publication in these proceedings was carefully reviewed and selected from 332 submissions. They are organized in the following topical sections: semantic web, social networks and recommendation systems; text processing and information retrieval; intelligent database systems; intelligent information systems; decision support and control systems; machine learning and data mining; multiple model approach to machine learning; innovations in intelligent systems and applications; bio-inspired optimization techniques and their applications; machine learning in biometrics and bioinformatics with applications; advanced data mining techniques and applications; collective intelligent systems for e-market trading, technology opportunity discovery and collaborative learning; intelligent information systems in security and defense; analysis of image, video and motion data in life sciences; augmented reality and 3D media; cloud based solutions; internet of things, big data and cloud computing; and artificial intelligent techniques and their application in engineering and operational research.