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Data-Driven 3D Facial Animation systematically describes the important techniques developed over the last ten years or so. Comprehensive in scope, the book provides an up-to-date reference source for those working in the facial animation field.
3D Modeling and Animation: Synthesis and Analysis Techniques for the Human Body covers the areas of modeling and animating 3D synthetic human models at a level that is useful to students, researchers, software developers and content generators. The reader will be presented with the latest, research-level, techniques for the analysis and synthesis of still and moving human bodies, with particular emphasis in facial and gesture characteristics.
Comprehensive coverage of critical issues related to information science and technology.
Affective Computing is a growing multidisciplinary field encompassing computer science, engineering, psychology, education, neuroscience, and many other disciplines. It explores how affective factors influence interactions between humans and technology, how affect sensing and affect generation techniques can inform our understanding of human affect, and on the design, implementation, and evaluation of systems that intricately involve affect at their core. The Oxford Handbook of Affective Computing will help both new and experienced researchers identify trends, concepts, methodologies, and applications in this burgeouning field. The volume features 41 chapters divided into five main sections: history and theory, detection, generation, methodologies, and applications. Section One begins with a look at the makings of AC and a historical review of the science of emotion. Chapters discuss the theoretical underpinnings of AC from an interdisciplinary perspective involving the affective, cognitive, social, media, and brain sciences. Section Two focuses on affect detection or affect recognition, which is one of the most commonly investigated areas in AC. Section Three examines aspects of affect generation including the synthesis of emotion and its expression via facial features, speech, postures and gestures. Cultural issues in affect generation are also discussed. Section Four features chapters on methodological issues in AC research, including data collection techniques, multimodal affect databases, emotion representation formats, crowdsourcing techniques, machine learning approaches, affect elicitation techniques, useful AC tools, and ethical issues in AC. Finally, Section Five highlights existing and future applications of AC in domains such as formal and informal learning, games, robotics, virtual reality, autism research, healthcare, cyberpsychology, music, deception, reflective writing, and cyberpsychology. With chapters authored by world leaders in each area, The Oxford Handbook of Affective Computing is suitable for use as a textbook in undergraduate or graduate courses in AC, and will serve as a valuable resource for students, researchers, and practitioners across the globe.
3D Face Processing: Modeling, Analysis and Synthesis introduces the frontiers of 3D face processing techniques. It reviews existing 3D face processing techniques, including techniques for 3D face geometry modeling; 3D face motion modeling; and 3D face motion tracking and animation. Then it discusses a unified framework for face modeling, analysis and synthesis. In this framework, the authors present new methods for modeling complex natural facial motion, as well as face appearance variations due to illumination and subtle motion. Then the authors apply the framework to face tracking, expression recognition and face avatar for HCI interface. They conclude this book with comments on future work in the 3D face processing framework. 3D Face Processing: Modeling, Analysis and Synthesis will interest those working in face processing for intelligent human computer interaction and video surveillance. It contains a comprehensive survey on existing face processing techniques, which can serve as a reference for students and researchers. It also covers in-depth discussion on face motion analysis and synthesis algorithms, which will benefit more advanced graduate students and researchers.
This book constitutes the proceedings of the 17th International Conference on Intelligent Virtual Agents, IVA 2017, held in Stockholm, Sweden, in August 2017. The 30 regular papers and 31 demo papers presented in this volume were carefully reviewed and selected from 78 submissions. The annual IVA conference represents the main interdisciplinary scientic forum for presenting research on modeling, developing, and evaluating intelligent virtual agents (IVAs) with a focus on communicative abilities and social behavior.
This book constitutes the refereed proceedings of the 17th International Conference on Speech and Computer, SPECOM 2015, held in Athens, Greece, in September 2015. The 59 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 104 initial submissions. The papers cover a wide range of topics in the area of computer speech processing such as recognition, synthesis, and understanding and related domains including signal processing, language and text processing, multi-modal speech processing or human-computer interaction.
These volumes present together a total of 64 revised full papers and 128 revised posters papers. The papers are organized in topical sections on camera calibration, stereo and pose, texture, face recognition, variational methods, tracking, geometry and calibration, lighting and focus, in the first volume. The papers of the second volume cover topics as detection and applications, statistics and kernels, segmentation, geometry and statistics, signal processing, and video processing.
Provides several examples of applications using the MPEG-4 Facial Animation standard, including video and speech analysis. Covers the implementation of the standard on both the encoding and decoding side. Contributors includes individuals instrumental in the standardization process.
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