This book provides comprehensive coverage of the latest trends/advances in subjective and objective quality evaluation for traditional visual signals, such as 2D images and video, as well as the most recent challenges for the field of multimedia quality assessment and processing, such as mobile video and social media. Readers will learn how to ensure the highest storage/delivery/ transmission quality of visual content (including image, video, graphics, animation, etc.) from the server to the consumer, under resource constraints, such as computation, bandwidth, storage space, battery life, etc.

This reference provides an in-depth discussion of the theory and application of lapped transforms (LTs). It explains how LTs can lead to a better complexity/performance trade-off than other transforms or filter bands used in signal processing. The text addresses the increased use LTs, especially with HDTV and how they may become the standard for high-quality audio coding.

This book offers a comprehensive and detailed guide to accomplishing and perfecting a photorealistic look in digital content across visual effects, architectural and product visualization, and games. Emmy award-winning VFX supervisor Eran Dinur offers readers a deeper understanding of the complex interplay of light, surfaces, atmospherics, and optical effects, and then discusses techniques to achieve this complexity in the digital realm, covering both 3D and 2D methodologies. In addition, the book features artwork, case studies, and interviews with leading artists in the fields of VFX, visualization, and games. Exploring color, integration, light and surface behaviour, atmospherics, shading, texturing, physically-based rendering, procedural modelling, compositing, matte painting, lens/camera effects, and much more, Dinur offers a compelling, elegant guide to achieving photorealism in digital media and creating imagery that is seamless from real footage. Its broad perspective makes this detailed guide suitable for VFX, visualization and game artists and students, as well as directors, architects, designers, and anyone who strives to achieve convincing, believable visuals in digital media.

This is an edited volume, written by well-recognized international researchers with extended chapter style versions of the best papers presented at the SITIS 2006 International Conference. This book presents the state-of-the-art and recent research results on the application of advanced signal processing techniques for improving the value of image and video data. It introduces new results on video coding on time-honored topic of securing image information. The book is designed for a professional audience composed of practitioners and researchers in industry. This book is also suitable for advanced-level students in computer science.

This book offers a comprehensive and detailed guide to accomplishing and perfecting a photorealistic look in digital content across visual effects, architectural and product visualization, and games. Emmy award-winning VFX supervisor Eran Dinur offers readers a deeper understanding of the complex interplay of light, surfaces, atmospherics, and optical effects, and then discusses techniques to achieve this complexity in the digital realm, covering both 3D and 2D methodologies. In addition, the book features artwork, case studies, and interviews with leading artists in the fields of VFX, visualization, and games. Exploring color, integration, light and surface behaviour, atmospherics, shading, texturing, physically-based rendering, procedural modelling, compositing, matte painting, lens/camera effects, and much more, Dinur offers a compelling, elegant guide to achieving photorealism in digital media and creating imagery that is seamless from real footage. Its broad perspective makes this detailed guide suitable for VFX, visualization and game artists and students, as well as directors, architects, designers, and anyone who strives to achieve convincing, believable visuals in digital media.

Video segmentation has become one of the core areas in visual signal processing research. The objective of Video Segmentation and Its Applications is to present the latest advances in video segmentation and analysis techniques while covering the theoretical approaches, real applications and methods being developed in the computer vision and video analysis community. The book will also provide researchers and practitioners a comprehensive understanding of state-of-the-art of video segmentation techniques and a resource for potential applications and successful practice.

This book presents how multimedia data analysis, information retrieval and indexing are central for comprehensive, personalized, adaptive quality care and the prolongation of independent living at home. With sophisticated technologies in monitoring, diagnosis, and treatment, multimodal data plays an increasingly central role in healthcare. Experts in computer vision, image processing, medical imaging, biomedical engineering, medical informatics, physical education and motor control, visual learning, nursing and human sciences, information retrieval, content based image retrieval, eHealth, information fusion, multimedia communications and human computer interaction come together to provide a thorough overview of multimedia analysis in medicine and daily life.

A wide variety of processes occur on multiple scales, either naturally or as a consequence of measurement. This book contains methodology for the analysis of data that arise from such multiscale processes. The book brings together a number of recent developments and makes them accessible to a wider audience. Taking a Bayesian approach allows for full accounting of uncertainty, and also addresses the delicate issue of uncertainty at multiple scales. The Bayesian approach also facilitates the use of knowledge from prior experience or data, and these methods can handle different amounts of prior knowledge at different scales, as often occurs in practice.

The book is aimed at statisticians, applied mathematicians, and engineers working on problems dealing with multiscale processes in time and/or space, such as in engineering, finance, and environmetrics. The book will also be of interest to those working on multiscale computation research. The main prerequisites are knowledge of Bayesian statistics and basic Markov chain Monte Carlo methods. A number of real-world examples are thoroughly analyzed in order to demonstrate the methods and to assist the readers in applying these methods to their own work. To further assist readers, the authors are making source code (for R) available for many of the basic methods discussed herein.

This book presents the use of efficient Evolutionary Computation (EC) algorithms for solving diverse real-world image processing and pattern recognition problems. It provides an overview of the different aspects of evolutionary methods in order to enable the reader in reaching a global understanding of the field and, in conducting studies on specific evolutionary techniques that are related to applications in image processing and pattern recognition. It explains the basic ideas of the proposed applications in a way that can also be understood by readers outside of the field. Image processing and pattern recognition practitioners who are not evolutionary computation researchers will appreciate the discussed techniques beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise on such areas. On the other hand, members of the evolutionary computation community can learn the way in which image processing and pattern recognition problems can be translated into an optimization task. The book has been structured so that each chapter can be read independently from the others. It can serve as reference book for students and researchers with basic knowledge in image processing and EC methods.

Hyperspectral Image Fusion is the first text dedicated to the fusion techniques for such a huge volume of data consisting of a very large number of images. This monograph brings out recent advances in the research in the area of visualization of hyperspectral data. It provides a set of pixel-based fusion techniques, each of which is based on a different framework and has its own advantages and disadvantages. The techniques are presented with complete details so that practitioners can easily implement them. It is also demonstrated how one can select only a few specific bands to speed up the process of fusion by exploiting spatial correlation within successive bands of the hyperspectral data. While the techniques for fusion of hyperspectral images are being developed, it is also important to establish a framework for objective assessment of such techniques. This monograph has a dedicated chapter describing various fusion performance measures that are applicable to hyperspectral image fusion. This monograph also presents a notion of consistency of a fusion technique which can be used to verify the suitability and applicability of a technique for fusion of a very large number of images. This book will be a highly useful resource to the students, researchers, academicians and practitioners in the specific area of hyperspectral image fusion, as well as generic image fusion.

This unique text/reference presents a fresh look at nonlinear processing through nonlinear eigenvalue analysis, highlighting how one-homogeneous convex functionals can induce nonlinear operators that can be analyzed within an eigenvalue framework. The text opens with an introduction to the mathematical background, together with a summary of classical variational algorithms for vision. This is followed by a focus on the foundations and applications of the new multi-scale representation based on non-linear eigenproblems. The book then concludes with a discussion of new numerical techniques for finding nonlinear eigenfunctions, and promising research directions beyond the convex case. Topics and features: introduces the classical Fourier transform and its associated operator and energy, and asks how these concepts can be generalized in the nonlinear case; reviews the basic mathematical notion, briefly outlining the use of variational and flow-based methods to solve image-processing and computer vision algorithms; describes the properties of the total variation (TV) functional, and how the concept of nonlinear eigenfunctions relate to convex functionals; provides a spectral framework for one-homogeneous functionals, and applies this framework for denoising, texture processing and image fusion; proposes novel ways to solve the nonlinear eigenvalue problem using special flows that converge to eigenfunctions; examines graph-based and nonlocal methods, for which a TV eigenvalue analysis gives rise to strong segmentation, clustering and classification algorithms; presents an approach to generalizing the nonlinear spectral concept beyond the convex case, based on pixel decay analysis; discusses relations to other branches of image processing, such as wavelets and dictionary based methods. This original work offers fascinating new insights into established signal processing techniques, integrating deep mathematical concepts from a range of different fields, which will be of great interest to all researchers involved with image processing and computer vision applications, as well as computations for more general scientific problems.

This book reviews the algorithms for processing geometric data, with a practical focus on important techniques not covered by traditional courses on computer vision and computer graphics. Features: presents an overview of the underlying mathematical theory, covering vector spaces, metric space, affine spaces, differential geometry, and finite difference methods for derivatives and differential equations; reviews geometry representations, including polygonal meshes, splines, and subdivision surfaces; examines techniques for computing curvature from polygonal meshes; describes algorithms for mesh smoothing, mesh parametrization, and mesh optimization and simplification; discusses point location databases and convex hulls of point sets; investigates the reconstruction of triangle meshes from point clouds, including methods for registration of point clouds and surface reconstruction; provides additional material at a supplementary website; includes self-study exercises throughout the text.

Video compression coding is the enabling technology behind a new wave of communication applications. From streaming internet video to broadcast digital television and digital cinema, the video codec is a key building block for a host of new multimedia applications and services. Video Codec Design sets out to de-mystify the subject of video coding and present a practical, design-based approach to this emerging field.

Featuring:

• Guidance on the practical design and implementation of video coding technology.
• Explanation of the major video coding standards, including MPEG-2, MPEG-4, H.263 and H.26L.
• Detailed coverage of key video coding techniques and core algorithms.
• Examination of critical design issues including transmission, Quality of Service and processing platforms.
• A wealth of illustrations and practical examples, including quantitative comparisons of design alternatives.

This text covers state-of-the-art color image and video enhancement techniques. The book examines the multivariate nature of color image/video data as it pertains to contrast enhancement, color correction (equalization, harmonization, normalization, balancing, constancy, etc.), noise removal and smoothing. This book also discusses color and contrast enhancement in vision sensors and applications of image and video enhancement.

This book presents the state-of-the-art in face detection and analysis. It outlines new research directions, including in particular psychology-based facial dynamics recognition, aimed at various applications such as behavior analysis, deception detection, and diagnosis of various psychological disorders. Topics of interest include face and facial landmark detection, face recognition, facial expression and emotion analysis, facial dynamics analysis, face classification, identification, and clustering, and gaze direction and head pose estimation, as well as applications of face analysis.

Digital image processing, an integral part of microscopy, is increasingly important to the fields of medicine and scientific research. This book provides a unique one-stop reference on the theory, technique, and applications of this technology.
Written by leading experts in the field, this book presents a unique practical perspective of state-of-the-art microscope image processing and the development of specialized algorithms. It contains in-depth analysis of methods coupled with the results of specific real-world experiments. Microscope Image Processing covers image digitization and display, object measurement and classification, autofocusing, and structured illumination.
Key Features:
- Detailed descriptions of many leading-edge methods and algorithms
- In-depth analysis of the method and experimental results, taken from real-life examples
- Emphasis on computational and algorithmic aspects of microscope image processing
-Advanced material on geometric, morphological, and wavelet image processing, fluorescence, three-dimensional and time-lapse microscopy, microscope image enhancement, MultiSpectral imaging, and image data management
This book is of interest to all scientists, engineers, clinicians, post-graduate fellows, and graduate students working in the fields of biology, medicine, chemistry, pharmacology, and other related fields. Anyone who uses microscopes in their work and needs to understand the methodologies and capabilities of the latest digital image processing techniques will find this book invaluable.
* Presents a unique practical perspective of state-of-the-art microcope image processing and the development of specialized algorithms.
*Each chapter includes in-depth analysis of methods coupled with the results of specific real-world experiments.
* Co-edited by Kenneth R. Castleman, world-renowned pioneer in digital image processing and author of two seminal textbooks on the subject.

This book presents and develops new reinforcement learning methods that enable fast and robust learning on robots in real-time. Robots have the potential to solve many problems in society, because of their ability to work in dangerous places doing necessary jobs that no one wants or is able to do. One barrier to their widespread deployment is that they are mainly limited to tasks where it is possible to hand-program behaviors for every situation that may be encountered. For robots to meet their potential, they need methods that enable them to learn and adapt to novel situations that they were not programmed for. Reinforcement learning (RL) is a paradigm for learning sequential decision making processes and could solve the problems of learning and adaptation on robots. This book identifies four key challenges that must be addressed for an RL algorithm to be practical for robotic control tasks. These RL for Robotics Challenges are: 1) it must learn in very few samples; 2) it must learn in domains with continuous state features; 3) it must handle sensor and/or actuator delays; and 4) it should continually select actions in real time. This book focuses on addressing all four of these challenges. In particular, this book is focused on time-constrained domains where the first challenge is critically important. In these domains, the agent's lifetime is not long enough for it to explore the domains thoroughly, and it must learn in very few samples.

Based on more than 10 years of teaching experience, Blanken and his coeditors have assembled all the topics that should be covered in advanced undergraduate or graduate courses on multimedia retrieval and multimedia databases. The single chapters of this textbook explain the general architecture of multimedia information retrieval systems and cover various metadata languages such as Dublin Core, RDF, or MPEG. The authors emphasize high-level features and show how these are used in mathematical models to support the retrieval process. For each chapter, there 's detail on further reading, and additional exercises and teaching material is available online.

This book will address the advances, applications, research results, and emerging areas of optics, photonics, computational approaches, nano-photonics, bio-photonics, with applications in information systems. The objectives are to bring together novel approaches, analysis, models, and technologies that enhance sensing, measurement, processing, interpretation, and visualization of information. The book will concentrate on new approaches to information systems, including integration of computational algorithms, bio-inspired models, photonics technologies, information security, bio-photonics, and nano-photonics. Applications include bio-photonics, digitally enhanced sensing and imaging systems, multi-dimensional optical imaging and image processing, bio-inspired imaging, 3D visualization, 3D displays, imaging on nano-scale, quantum optics, super resolution imaging, photonics for biological applications, microscopy, information optics, and holographic information systems.

"Advances in Imaging and Electron Physics" merges two long-running serials-Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. This series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science and digital image processing, electromagnetic wave propagation, electron microscopy, and the computing methods used in all these domains.
An important feature of these Advances is that the subjects are written in such a way that they can be understood by readers from other specialities.

Through a series of step-by-step tutorials and numerous hands-on exercises, this book aims to equip the reader with both a good understanding of the importance of space in the abstract world of engineers and the ability to create a model of a product in virtual space - a skill essential for any designer or engineer who needs to present ideas concerning a particular product within a professional environment. The exercises progress logically from the simple to the more complex; while Solid Works or NX is the software used, the underlying philosophy is applicable to all modeling software. In each case, the explanation covers the entire procedure from the basic idea and production capabilities through to the real model; the conversion from 3D model to 2D manufacturing drawing is also clearly explained. Topics covered include modeling of prism, axisymmetric, symmetric and sophisticated shapes; digitization of physical models using modeling software; creation of a CAD model starting from a physical model; free form surface modeling; modeling of product assemblies following bottom-up and top-down principles; and the presentation of a product in accordance with the rules of technical documentation. This book, which includes more than 500 figures, will be ideal for students wishing to gain a sound grasp of space modeling techniques. Academics and professionals will find it to be an excellent teaching and research aid, and an easy-to-use guide.

This book presents a comprehensive treatise on Riemannian geometric computations and related statistical inferences in several computer vision problems. This edited volume includes chapter contributions from leading figures in the field of computer vision who are applying Riemannian geometric approaches in problems such as face recognition, activity recognition, object detection, biomedical image analysis, and structure-from-motion. Some of the mathematical entities that necessitate a geometric analysis include rotation matrices (e.g. in modeling camera motion), stick figures (e.g. for activity recognition), subspace comparisons (e.g. in face recognition), symmetric positive-definite matrices (e.g. in diffusion tensor imaging), and function-spaces (e.g. in studying shapes of closed contours).

The creation and consumption of content, especially visual content, is ingrained into our modern world. This book contains a collection of texts centered on the evaluation of image retrieval systems. To enable reproducible evaluation we must create standardized benchmarks and evaluation methodologies. The individual chapters in this book highlight major issues and challenges in evaluating image retrieval systems and describe various initiatives that provide researchers with the necessary evaluation resources. In particular they describe activities within ImageCLEF, an initiative to evaluate cross-language image retrieval systems which has been running as part of the Cross Language Evaluation Forum (CLEF) since 2003.

To this end, the editors collected contributions from a range of people: those involved directly with ImageCLEF, such as the organizers of specific image retrieval or annotation tasks; participants who have developed techniques to tackle the challenges set forth by the organizers; and people from industry and academia involved with image retrieval and evaluation generally.

Mostly written for researchers in academia and industry, the book stresses the importance of combing textual and visual information - a multimodal approach - for effective retrieval. It provides the reader with clear ideas about information retrieval and its evaluation in contexts and domains such as healthcare, robot vision, press photography, and the Web.

This is the first book which informs about recent progress in biomechanics, computer vision and computer graphics - all in one volume. Researchers from these areas have contributed to this book to promote the establishment of human motion research as a multi-facetted discipline and to improve the exchange of ideas and concepts between these three areas. The book combines carefully written reviews with detailed reports on recent progress in research.

This book covers up-to-date methods and algorithms for the automated analysis of engineering drawings and digital cartographic maps. The Non-Deterministic Agent System (NDAS) offers a parallel computational approach to such image analysis. The book describes techniques suitable for persistent and explicit knowledge representation for engineering drawings and digital maps. It also highlights more specific techniques, e.g., applying robot navigation and mapping methods to this problem. Also included are more detailed accounts of the use of unsupervised segmentation algorithms to map images. Finally, all these threads are woven together in two related systems: NDAS and AMAM (Automatic Map Analysis Module).