This volume collects the papers accepted for presentation at the Second European Conference on Computer Vision, held in Santa Margherita Ligure, Italy, May 19-22, 1992. Sixteen long papers, 41 short papers and 48 posters were selected from 308 submissions. The contributions are structured into 14 sections reflecting the major research topics in computer vision currently investigated worldwide. The sections are entitled: features, color, calibration and matching, depth, stereo-motion, tracking, active vision, binocular heads, curved surfaces and objects, reconstruction and shape, recognition, and applications.

Lewis Carroll once wrote a story about a king who wanted a very accurate map of his kingdom. The king had a pathologically fastidious eye for detail and consequently decided that the map was to be produced at a scale of 1:1. The scribes dutifully set to and, in time, the map was made. The map carried details of every tree, every rock and every blade of grass throughout the entire land. The problem occurred when they tried to use -it. First of all, the map was extraordinarily difficult to open out and line up with the countryside. Its sheer bulk meant that it took whole armies to carry it and a great host of bureaucrats and technicians to maintain the information. Such was the detail of the map that as soon as the wind blew strongly, whole sections needed to be redrawn. What was worse was that all the farmers protested because the map completely cut out the light from the sun and all the crops died. Eventually the howls of protest became so strong that the king was forced to take action. He did away with the old paper copy and decided to use the kingdom itself as the map. All lived happily ever after. There are, at least, two morals to this tale. First, you are almost certainly doomed to failure if you do not get the representation of the problem right.

A machine vision system should be able to analyze images and produce descriptions of what it "sees." The descriptions should capture the aspects of the objects being imaged and be useful for accomplishing some specific tasks. In this volume a number of subjects are discussed. They include theoretical aspects which focus on shape analysis, special architectures, 3-D image decomposition, inspection by machine vision, and others. Applications include geophysical image analysis, robotics, sparse image understanding, biomedical applications. An ample survey of the present industrial applications is also provided.

A collection of papers on computer vision research in Euro- pe, with sections on image features, stereo and reconstruc- tion, optical flow, motion, structure from motion, tracking, stereo and motion, features and shape, shape description, and recognition and matching.

Das Buch fuhrt auf einfache und verstandliche Weise in die Bayes-Statistik ein. Ausgehend vom Bayes-Theorem werden die Schatzung unbekannter Parameter, die Festlegung von Konfidenzregionen fur die unbekannten Parameter und die Prufung von Hypothesen fur die Parameter abgeleitet. Angewendet werden die Verfahren fur die Parameterschatzung im linearen Modell, fur die Parameterschatzung, die sich robust gegenuber Ausreissern in den Beobachtungen verhalt, fur die Pradiktion und Filterung, die Varianz- und Kovarianzkomponentenschatzung und die Mustererkennung. Fur Entscheidungen in Systemen mit Unsicherheiten dienen Bayes-Netze. Lassen sich notwendige Integrale analytisch nicht losen, werden numerische Verfahren mit Hilfe von Zufallswerten eingesetzt."

Researchers, academicians and professionals expone in this book their research in the application of intelligent computing techniques to software engineering. As software systems are becoming larger and complex, software engineering tasks become increasingly costly and prone to errors. Evolutionary algorithms, machine learning approaches, meta-heuristic algorithms, and others techniques can help the effi ciency of software engineering.

Many persons have helped the author with comments and corrections, and I would like to mention D. E. McClure, I. Frolow, J. Silverstein, D. Town, and especially W. Freiberger for his helpful suggestions and encouragement. The work in Chapters 6 and 7 has been influenced and stimulated by discussions with other members of the Center for Neural Sciences, especially with L. Cooper and H. Kucera. I would like to thank F. John, J. P. LaSalle, L. Sirovich, and G. Whitham for accepting the manuscript for the series Applied Mathematical Sciences published by Springer-Verlag. This research project has been supported by the Division of Mathematical and Computer Sciences of the National Science Foundation and (the work on language abduction, pattern processors, and patterns in program behavior) by the Information Systems Program of the Office of Naval Research. I greatly appreciate the understanding and positive interest shown by John Pasta, Kent Curtiss, Bruce Barnes, Sally Sedelov vi PREFACE and Bob Agins of the Foundation, and by Marvin Denicoff of the Office of Naval Research. I am indebted to Mrs. E. Fonseca for her untiring and careful preparation of the manuscript, to Miss E. Addison for her skillful help with the many diagrams, and to S.V. Spinacci for the final typing. I gratefully acknowledge permission to reproduce figures, as mentioned in the text, from Cambridge University Press and from Hayden Book Company. Also, to Professor J. Carbury for permission to use his illustration on page 704.

Image Segmentation Summarizes and improves new theory, methods, and applications of current image segmentation approaches, written by leaders in the field The process of image segmentation divides an image into different regions based on the characteristics of pixels, resulting in a simplified image that can be more efficiently analyzed. Image segmentation has wide applications in numerous fields ranging from industry detection and bio-medicine to intelligent transportation and architecture. Image Segmentation: Principles, Techniques, and Applications is an up-to-date collection of recent techniques and methods devoted to the field of computer vision. Covering fundamental concepts, new theories and approaches, and a variety of practical applications including medical imaging, remote sensing, fuzzy clustering, and watershed transform. In-depth chapters present innovative methods developed by the authors--such as convolutional neural networks, graph convolutional networks, deformable convolution, and model compression--to assist graduate students and researchers apply and improve image segmentation in their work. Describes basic principles of image segmentation and related mathematical methods such as clustering, neural networks, and mathematical morphology. Introduces new methods for achieving rapid and accurate image segmentation based on classic image processing and machine learning theory. Presents techniques for improved convolutional neural networks for scene segmentation, object recognition, and change detection, etc. Highlights the effect of image segmentation in various application scenarios such as traffic image analysis, medical image analysis, remote sensing applications, and material analysis, etc. Image Segmentation: Principles, Techniques, and Applications is an essential resource for undergraduate and graduate courses such as image and video processing, computer vision, and digital signal processing, as well as researchers working in computer vision and image analysis looking to improve their techniques and methods.

In dem Buch werden Methoden vorgestellt, mit denen ubersehenes IT-Potenzial in Organisation genutzt werden kann. Dabei geht die Autorin davon aus, dass das Wissen bereits vorhanden ist und nur gehoben werden muss. Mit Checklisten und Tipps fur die Umsetzung."

Die automatische Auswertung von Signalen spielt in der modernen Informationstechnik eine grosse Rolle. Dieses Lehrbuch bietet, ausgehend von der Reprasentation des Signals im Merkmalraum, die Beschreibung wichtiger Klassifikationsverfahren. Dazu zahlen Linear- und Bayes Klassifikatoren, Supportvektormaschinen, Klassifikatoren auf der Basis von Gaussian-Mixture-Modellen und Hidden-Markov-Modellen sowie Klassenfolgenklassifikatoren.Weiterhin werden wichtige Grundlagen der Automatentheorie (Finite State Machines) sowie ausgewahlte maschinelle Lernverfahren dargestellt.Die Darstellung setzt die Verfahren zur Merkmalgewinnung voraus, die im ersten Band vermittelt wurden, so dass das Gesamtwerk eine umfassende Beschreibung der Kette darstellt, die in modernen Systemen der Informationsverarbeitung von der Signalerfassung bis hin zum Klassifikationsergebnis fuhrt.

The typical computational approach to object understanding derives shape information from the 2D outline of the objects. For complex object structures, however, such a planar approach cannot determine object shape; the structural edges have to be encoded in terms of their full 3D spatial configuration. Computer Vision: From Surfaces to 3D Objects is the first book to take a full approach to the challenging issue of veridical 3D object representation. It introduces mathematical and conceptual advances that offer an unprecedented framework for analyzing the complex scene structure of the world. An Unprecedented Framework for Complex Object Representation Presenting the material from both computational and neural implementation perspectives, the book covers novel analytic techniques for all levels of the surface representation problem. The cutting-edge contributions in this work run the gamut from the basic issue of the ground plane for surface estimation through mid-level analyses of surface segmentation processes to complex Riemannian space methods for representing and evaluating surfaces. State-of-the-Art 3D Surface and Object Representation This well-illustrated book takes a fresh look at the issue of 3D object representation. It provides a comprehensive survey of current approaches to the computational reconstruction of surface structure in the visual scene.

This book focuses on the use of AI/ML-based techniques to solve issues related to IoT-based environments, as well as their applications. It addresses, among others, signal detection, channel modeling, resource optimization, routing protocol design, transport layer optimization, user/application behavior prediction, software-defi ned networking, congestion control, communication network optimization, security, and anomaly detection.

This book addresses emerging issues in usability, interface design, human-computer interaction, user experience and assistive technology. It highlights research aimed at understanding human interactions with products, services and systems and focuses on finding effective approaches for improving the user experience. It also discusses key issues in designing and providing assistive devices and services for individuals with disabilities or impairment, offering them support with mobility, communication, positioning, environmental control and daily living. The book covers modeling as well as innovative design concepts, with a special emphasis on user-centered design, and design for specific populations, particularly the elderly. Further topics include virtual reality, digital environments, gaming, heuristic evaluation and forms of device interface feedback (e.g. visual and haptic). Based on the AHFE 2021 Conferences on Usability and User Experience, Human Factors and Wearable Technologies, Human Factors in Virtual Environments and Game Design, and Human Factors and Assistive Technology, held virtually on 25-29 July, 2021, from USA, this book provides academics and professionals with an extensive source of information and a timely guide to tools, applications and future challenges in these fields.

The typical computational approach to object understanding derives shape information from the 2D outline of the objects. For complex object structures, however, such a planar approach cannot determine object shape; the structural edges have to be encoded in terms of their full 3D spatial configuration. Computer Vision: From Surfaces to 3D Objects is the first book to take a full approach to the challenging issue of veridical 3D object representation. It introduces mathematical and conceptual advances that offer an unprecedented framework for analyzing the complex scene structure of the world. An Unprecedented Framework for Complex Object Representation Presenting the material from both computational and neural implementation perspectives, the book covers novel analytic techniques for all levels of the surface representation problem. The cutting-edge contributions in this work run the gamut from the basic issue of the ground plane for surface estimation through mid-level analyses of surface segmentation processes to complex Riemannian space methods for representing and evaluating surfaces. State-of-the-Art 3D Surface and Object Representation This well-illustrated book takes a fresh look at the issue of 3D object representation. It provides a comprehensive survey of current approaches to the computational reconstruction of surface structure in the visual scene.

The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23-27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.

This two volume proceedings, LNCS 13445 and 13446, constitutes the refereed proceedings of the 9th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics, XR Salento 2022, held in Lecce, Italy, July 6-8, 2022. Due to COVID-19 pandemic the conference was held as a hybrid conference.The 42 full and 16 short papers were carefully reviewed and selected from 84 submissions. The papers discuss key issues, approaches, ideas, open problems, innovative applications and trends in virtual reality, augmented reality, mixed reality, applications in cultural heritage, in medicine, in education, and in industry.

Nel 1925, Economo e Koskinas pubblicarono l'atlante piu accurato e completo sulla citoarchitettonica della corteccia cerebrale umana mai realizzato. Una sintesi del contenuto dell'atlante venne in seguito resa disponibile in tedesco e tradotta in italiano, inglese e francese. Il valore scientifico di quest'opera e divenuto piu significativo negli ultimi vent'anni con l'avvento delle tecniche di neuroimaging funzionale, le quali consentono persino di rilevare specifici focolai di attivazione nella corteccia cerebrale umana durante l'esecuzione di compiti cognitivi. Questa riedizione in italiano e stata ampliata rispetto all'originale con l'aggiunta della mappa dei solchi e dei giri del cervello. Inoltre, e stata inclusa la tabella delle corrispondenze tra le aree individuate da Economo e Koskinas e quelle descritte da Brodmann. Il volume sara di grande interesse per tutti coloro che desiderano approfondire la relazione tra la struttura del cervello e le sue funzioni; rappresentera inoltre un utile strumento di lavoro per i professionisti che utilizzano le neuroimmagini nella loro pratica quotidiana, quali neurofisiologi, neuropsicologi, neuroradiologi, neurologi e neurochirurghi.

Discover the methods and techniques required for creating immersive design visualization for industry. This book proposes ways for industry-oriented design visualization from scratch. This includes fundamentals of creative and immersive technology; tools and techniques for architectural visualization; design visualization with Autodesk Maya; PBR integration; and texturing, material design, and integration into UE4 for immersive design visualization. You'll to dive into design and visualization, from planning to execution. You will start with the basics, such as an introduction to design visualization as well as to the software you will be using. You will next learn to create assets such as virtual worlds and texturing, and integrate them with Unreal Engine 4. Finally, there is a capstone project for you to make your own immersive visualization scene. By the end of the book you'll be able to create assets for use in industries such as game development, entertainment, architecture, design engineering, and digital education. What You Will Learn Gain the fundamentals of immersive design visualization Master design visualization with Autodesk Maya Study interactive visualization with UE4 Create your immersive design portfolio Who This Book Is For Beginning-intermediate learners from the fields of animation, visual art, and computer graphics as well as design visualization, game technology, and virtual reality integration.

This is the first book that focuses entirely on the fundamental questions in visualization. Unlike other existing books in the field, it contains discussions that go far beyond individual visual representations and individual visualization algorithms. It offers a collection of investigative discourses that probe these questions from different perspectives, including concepts that help frame these questions and their potential answers, mathematical methods that underpin the scientific reasoning of these questions, empirical methods that facilitate the validation and falsification of potential answers, and case studies that stimulate hypotheses about potential answers while providing practical evidence for such hypotheses. Readers are not instructed to follow a specific theory, but their attention is brought to a broad range of schools of thoughts and different ways of investigating fundamental questions. As such, the book represents the by now most significant collective effort for gathering a large collection of discourses on the foundation of data visualization. Data visualization is a relatively young scientific discipline. Over the last three decades, a large collection of computer-supported visualization techniques have been developed, and the merits and benefits of using these techniques have been evidenced by numerous applications in practice. These technical advancements have given rise to the scientific curiosity about some fundamental questions such as why and how visualization works, when it is useful or effective and when it is not, what are the primary factors affecting its usefulness and effectiveness, and so on. This book signifies timely and exciting opportunities to answer such fundamental questions by building on the wealth of knowledge and experience accumulated in developing and deploying visualization technology in practice.

This three-volume set, LNAI 13629, LNAI 13630, and LNAI 13631 constitutes the thoroughly refereed proceedings of the 19th Pacific Rim Conference on Artificial Intelligence, PRICAI 2022, held in Shangai, China, in November 10-13, 2022. The 91 full papers and 39 short papers presented in these volumes were carefully reviewed and selected from 432 submissions. PRICAI covers a wide range of topics in the areas of social and economic importance for countries in the Pacific Rim: artificial intelligence, machine learning, natural language processing, knowledge representation and reasoning, planning and scheduling, computer vision, distributed artificial intelligence, search methodologies, etc.

This book constitutes the proceedings of the First Workshop on Computational Mathematics Modeling in Cancer Analysis (CMMCA2022), held in conjunction with MICCAI 2022, in Singapore in September 2022. Due to the COVID-19 pandemic restrictions, the CMMCA2022 was held virtually. DALI 2022 accepted 15 papers from the 16 submissions that were reviewed. A major focus of CMMCA2022 is to identify new cutting-edge techniques and their applications in cancer data analysis in response to trends and challenges in theoretical, computational and applied aspects of mathematics in cancer data analysis.

The 4-volume set LNCS 13534, 13535, 13536 and 13537 constitutes the refereed proceedings of the 5th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2022, held in Shenzhen, China, in November 2022. The 233 full papers presented were carefully reviewed and selected from 564 submissions. The papers have been organized in the following topical sections: Theories and Feature Extraction; Machine learning, Multimedia and Multimodal; Optimization and Neural Network and Deep Learning; Biomedical Image Processing and Analysis; Pattern Classification and Clustering; 3D Computer Vision and Reconstruction, Robots and Autonomous Driving; Recognition, Remote Sensing; Vision Analysis and Understanding; Image Processing and Low-level Vision; Object Detection, Segmentation and Tracking.

This book constitutes the refereed proceedings of the 10th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2022, held as part of Evo* 2022, in April 2022, co-located with the Evo* 2022 events, EvoCOP, EvoApplications, and EuroGP. The 20 full papers and 6 short papers presented in this book were carefully reviewed and selected from 66 submissions. They cover a wide range of topics and application areas, including generative approaches to music and visual art, deep learning, and architecture.