Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques. Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.
Einführung in die Verarbeitung und Analyse digitaler Bilder
Author: Lutz Priese
Der Autor erläutert in dieser Einführung auf Bachelorniveau die in der Computer Vision verwendeten technischen Ausdrücke: Grundlagen des menschlichen Sehens, Farbe, exakte Begriffsbestimmungen zum Thema "Bild", Transformationen, lineare und nicht-lineare Filter, Fouriertransformation, Morphologie, Merkmale im Bild wie Kanten, Ecken, geometrische Formen mittels Hough-Transformation, diverse Hüllen und Skelettierung. Ferner höhere Merkmale wie SIFT, Shape-Context und statistische Merkmale, Texturmerkmale. Die Bestimmung von Segmenten (zusammenhängende Regionen ähnlicher Farben oder Grauwerte) wird in einem eigenen Kapitel ausführlich behandelt.
8th International Conference, ICVS 2011, Sophia Antipolis, France, September 20-22, 2011, Proceedings
Author: James L. Crowley,Bruce Draper,Monique Thonnat
Publisher: Springer Science & Business Media
This book constitutes the refereed proceedings of the 8th International Conference on Computer Vision Systems, ICVS 2011, held in Sophia Antipolis, France, in September 2009. The 22 revised papers presented were carefully reviewed and selected from 58 submissions. The papers are organized in topical sections on vision systems, control of perception, performance evaluation, activity recognition, and knowledge directed vision.
Dieses Lehrbuch behandelt die Grundlagen, Algorithmen und Anwendungen eines Teilbereichs der digitalen Bildverarbeitung: die Szenenanalyse bzw. die 3D-Bildanalyse. Methoden der Bildbearbeitung und der Musteranalyse stellen Werkzeuge dar, um aus den Bildinformationen von dreidimensionalen Objekten Ausgangsdaten für die Bildinterpretation zu erzeugen.
This book contains a selection of papers which were presented at the Vision Interface '92 Conference. It also includes several invited articles from prominent researchers in the field, suggesting future directions in Computer Vision.
Computer Vision Systems is a collection of papers presented at the Workshop on Computer Vision Systems held at the University of Massachusetts in Amherst, Massachusetts, on June 1-3, 1977. Contributors discuss the breadth of problems that must be taken into account in the development of general computer vision systems. Topics covered include the application of system engineering techniques to the design of artificial intelligence systems; representation and segmentation of natural scenes; and pragmatic aspects of machine vision. Psychophysical measures of representation and interpretation are also considered. This monograph is divided into four sections: Issues and Research Strategies, Segmentation, Theory and Psychology, and Systems. The first chapter explores the problem of recovering the intrinsic characteristics of scenes from images, along with its implications for machine and human vision. The discussion then turns to special-purpose low-level vision systems that can be flexibly reconfigured as the need arises; design, development, and implementation of large systems from the human engineering point of view; and representation of visual information. The next section examines hierarchical relaxation for waveform parsing; the topology and semantics of intensity arrays; and visual images as spatial representations in active memory. The use of edge cues to recognize real-world objects is also analyzed. This text will be a useful resource for systems designers, computer engineers, and scientists as well as psychologists.
Using a progressive intuitive/mathematical approach, this introduction to computer vision provides necessary theory and examples for practitioners who work in fields where significant information must be extracted automatically from images-- including those interested in multimedia, art and design, geographic information systems, and image databases, in addition to the traditional areas of automation, image science, medical imaging, remote sensing and computer cartography. The book provides a basic set of fundamental concepts, (representations of image information, extraction of 3D scene information from 2D images, etc.) algorithms for analyzing images, and discusses some of the exciting evolving application areas of computer vision. The approach is language and software independent, and includes two significant commercial case studies. Imaging and Image Representation. Binary Image Analysis. Pattern Recognition Concepts. Filtering and Enhancing Images. Color and Shading. Texture. Content-Based Image Retrieval. Motion from 2D Image Sequences. Image Segmentation. Matching in 2D. Perceiving 3D from 2D Images. 3D Sensing and Object Pose Computation. 3D Models and Matching. Virtual Reality. Case Studies. For practitioners in any field where information must be extracted automatically from images.
Andrea Fossati,Juergen Gall,Helmut Grabner,Xiaofeng Ren,Kurt Konolige
Author: Andrea Fossati,Juergen Gall,Helmut Grabner,Xiaofeng Ren,Kurt Konolige
Publisher: Springer Science & Business Media
The potential of consumer depth cameras extends well beyond entertainment and gaming, to real-world commercial applications. This authoritative text reviews the scope and impact of this rapidly growing field, describing the most promising Kinect-based research activities, discussing significant current challenges, and showcasing exciting applications. Features: presents contributions from an international selection of preeminent authorities in their fields, from both academic and corporate research; addresses the classic problem of multi-view geometry of how to correlate images from different viewpoints to simultaneously estimate camera poses and world points; examines human pose estimation using video-rate depth images for gaming, motion capture, 3D human body scans, and hand pose recognition for sign language parsing; provides a review of approaches to various recognition problems, including category and instance learning of objects, and human activity recognition; with a Foreword by Dr. Jamie Shotton.
7th International Conference on Computer Vision Systems, ICVS 2009 Liège, Belgium, October 13-15, 2009, Proceedings
Author: Mario Fritz,Bernt Schiele,Justus H. Piater
Publisher: Springer Science & Business Media
This book constitutes the refereed proceedings of the 7th International Conference on Computer Vision Systems, ICVS 2009, held in Liege, Belgium, October 13-15, 2009. The 21 papers for oral presentation presented together with 24 poster presentations and 2 invited papers were carefully reviewed and selected from 96 submissions. The papers are organized in topical sections on human-machine-interaction, sensors, features and representations, stereo, 3D and optical flow, calibration and registration, mobile and autonomous systems, evaluation, studies and applications, learning, recognition and adaption.
Theo Gevers,Arjan Gijsenij,Joost van de Weijer,Jan-Mark Geusebroek
Author: Theo Gevers,Arjan Gijsenij,Joost van de Weijer,Jan-Mark Geusebroek
Publisher: John Wiley & Sons
Category: Technology & Engineering
While the field of computer vision drives many of today’sdigital technologies and communication networks, the topic of colorhas emerged only recently in most computer vision applications. Oneof the most extensive works to date on color in computer vision,this book provides a complete set of tools for working with colorin the field of image understanding. Based on the authors’ intense collaboration for more thana decade and drawing on the latest thinking in the field ofcomputer science, the book integrates topics from color science andcomputer vision, clearly linking theories, techniques, machinelearning, and applications. The fundamental basics, sampleapplications, and downloadable versions of the software and datasets are also included. Clear, thorough, and practical, Colorin Computer Vision explains: Computer vision, including color-driven algorithms andquantitative results of various state-of-the-art methods Color science topics such as color systems, color reflectionmechanisms, color invariance, and color constancy Digital image processing, including edge detection, featureextraction, image segmentation, and image transformations Signal processing techniques for the development of both imageprocessing and machine learning Robotics and artificial intelligence, including such topics assupervised learning and classifiers for object and scenecategorization Researchers and professionals in computer science,computer vision, color science, electrical engineering, and signalprocessing will learn how to implement color in computer visionapplications and gain insight into future developments in thisdynamic and expanding field.
This edited volume explores several issues relating to parametric segmentation including robust operations, model selection criteria and automatic model selection, plus 2D and 3D scene segmentation. Emphasis is placed on robust model selection with techniques such as robust Mallows Cp, least K-th order statistical model fitting (LKS), and robust regression receiving much attention. With contributions from leading researchers, this is a valuable resource for researchers and graduated students working in computer vision, pattern recognition, image processing and robotics.
A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.
Workshop Proceedings, Killarney, Ireland, September 9/10, 1991
Author: David Vernon
Publisher: Springer Science & Business Media
This volume assesses approaches to the construction of computer vision systems. It shows that there is a spectrum of approaches with different degrees of maturity and robustness. The useful exploitation of computer vision in industry and elsewhere and the development of the discipline itself depend on understanding the way these approaches influence one another. The chief topic discussed is autonomy.True autonomy may not be achievable in machines in the near future, and the workshop concluded that it may be more desirable - and is certainly more pragmatic - to leave a person in the processing loop. The second conclusion of the workshop concerns the manner in which a system is designedfor an application. It was agreed that designers should first specify the required functionality, then identify the knowledge appropriate to that task, and finally choose the appropriate techniques and algorithms. The third conclusion concerns the methodologies employed in developing vision systems: craft, engineering, and science are mutually relevant and contribute to one another. The contributors place heavy emphasis on providing the reader with concrete examples of operational systems. The book is based on a workshop held as part of the activities of an ESPRIT Basic Research Action.
Computer vision is the science and technology of machines that see. As a scientific discipline, computer vision is concerned with the theory and technology for building artificial systems that obtain information from images. The image data can take many forms, such as a video sequence, views from multiple cameras, or multi-dimensional data from a medical scanner. As a technological discipline, computer vision seeks to apply the theories and models of computer vision to the construction of computer vision systems. Examples of applications of computer vision systems include systems for controlling processes (e.g. an industrial robot or an autonomous vehicle). Detecting events (e.g. for visual surveillance). Organizing information (e.g. for indexing databases of images and image sequences), Modeling objects or environments (e.g. industrial inspection, medical image analysis or topographical modeling), Interaction (e.g. as the input to a device for computer-human interaction). Computer vision can also be described as a complement (but not necessarily the opposite) of biological vision. In biological vision, the visual perception of humans and various animals are studied, resulting in models of how these systems operate in terms of physiological processes. Computer vision, on the other hand, studies and describes artificial vision system that are implemented in software and/or hardware. Interdisciplinary exchange between biological and computer vision has proven increasingly fruitful for both fields. Sub-domains of computer vision include scene reconstruction, event detection, tracking, object recognition, learning, indexing, ego-motion and image restoration. This new book presents leading-edge new research from around the world.
AlpeshKumar Ranchordas,Joao Madeiras Pereira,Hélder J. Araújo,Joao Tavares
International Joint Conference, VISIGRAPP 2009, Lisboa, Portugal, February 5-8, 2009. Revised Selected Papers
Author: AlpeshKumar Ranchordas,Joao Madeiras Pereira,Hélder J. Araújo,Joao Tavares
Publisher: Springer Science & Business Media
This book includes extended versions of the selected papers from VISIGRAPP 2009, the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, which was held in Lisbon, Portugal, during February 5–8, 2009 and organized by the Institute for Systems and Technologies of Information, Control and Communication (INSTICC). VISIGRAPP comprises three component conferences, namely, the International Conference on Computer Vision Theory and Applications (VISAPP), the International Conference on Computer Graphics Theory and Applications (GRAPP), and the International Conference on Imaging Theory and Applications (IMAGAPP). VISIGRAPP received a total of 422 paper submissions from more than 50 co- tries. From these, and after a rigorous double-blind evaluation method, 72 papers were published as full papers. These figures show that this conference is now an - tablished venue for researchers in the broad fields of computer vision, computer graphics and image analysis. From the full papers, 25 were selected for inclusion in this book. The selection process was based on the scores assigned by the Program Committee reviewers as well as the Session Chairs. After selection, the papers were further revised and extended by the authors. Our gratitude goes to all contributors and referees, without whom this book would not have been possible.
Computer Vision and Image Processing contains review papers from the Computer Vision, Graphics, and Image Processing volume covering a large variety of vision-related topics. Organized into five parts encompassing 26 chapters, the book covers topics on image-level operations and architectures; image representation and recognition; and three-dimensional imaging. The introductory part of this book is concerned with the end-to-end performance of image gathering and processing for high-resolution edge detection. It proposes methods using mathematical morphology to provide a complete edge detection process that may be used with any slope approximating operator. This part also discusses the automatic control of low-level robot vision, presents an image partitioning method suited for parallel implementation, and describes invariant architectures for low-level vision. The subsequent two sections present significant topics on image representation and recognition. Topics covered include the use of the primitives chain code; the geometric properties of the generalized cone; efficient rendering and structural-statistical character recognition algorithms; multi-level thresholding for image segmentation; knowledge-based object recognition system; and shape decomposition method based on perceptual structure. The fourth part describes a rule-based expert system for recovering three-dimensional shape and orientation. A procedure of intensity-guided range sensing to gain insights on the concept of cooperative-and-iterative strategy is also presented in this part. The concluding part contains supplementary texts on texture segmentation using topographic labels and an improved algorithm for labeling connected components in a binary image. Additional algorithms for three-dimensional motion parameter determination and surface tracking in three-dimensional binary images are also provided.
Workshop Proceedings Barcelona, Spain, September 1991
Author: Eduard Montseny,Joan Frau
Publisher: Springer Science & Business Media
Computer vision falls short of human vision in two respects: execution time and intelligent interpretation. This book addresses the question of execution time. It is based on a workshop on specialized processors for real-time image analysis, held as part of the activities of an ESPRIT Basic Research Action, the Working Group on Vision. The aim of the book is to examine the state of the art in vision-oriented computers. Two approaches are distinguished: multiprocessor systems and fine-grain massively parallel computers. The development of fine-grain machines has become more important over the last decade, but one of the main conclusions of the workshop is that this does not imply the replacement of multiprocessor machines. The book is divided into four parts. Part 1 introduces different architectures for vision: associative and pyramid processors as examples of fine-grain machines and a workstation with bus-oriented network topology as an example of a multiprocessor system. Parts 2 and 3 deal with the design and development of dedicated and specialized architectures. Part 4 is mainly devoted to applications, including road segmentation, mobile robot guidance and navigation, reconstruction and identification of 3D objects, and motion estimation.
The three volume set LNCS 5994, LNCS 5995, and LNCS 5996 constitutes the thoroughly refereed post-conference proceedings of the 9th Asian Conference on Computer Vision, ACCV 2009, held in Xi'an, China, in September 2009. The 35 revised full papers and 130 revised poster papers of the three volumes were carefully reviewed and seleceted from 670 submissions. The papers are organized in topical sections on multiple view and stereo, face and pose analysis, motion analysis and tracking, segmentation, feature extraction and object detection, image enhancement and visual attention, machine learning algorithms for vision, object categorization and face recognition, biometrics and surveillance, stereo, motion analysis, and tracking, segmentation, detection, color and texture, as well as machine learning, recognition, biometrics and surveillance.
This indispensable text introduces the foundations of three-dimensional computer vision and describes recent contributions to the field. Fully revised and updated, this much-anticipated new edition reviews a range of triangulation-based methods, including linear and bundle adjustment based approaches to scene reconstruction and camera calibration, stereo vision, point cloud segmentation, and pose estimation of rigid, articulated, and flexible objects. Also covered are intensity-based techniques that evaluate the pixel grey values in the image to infer three-dimensional scene structure, and point spread function based approaches that exploit the effect of the optical system. The text shows how methods which integrate these concepts are able to increase reconstruction accuracy and robustness, describing applications in industrial quality inspection and metrology, human-robot interaction, and remote sensing.
This monograph by one of the world's leading vision researchers provides a thorough, mathematically rigorous exposition of a broad and vital area in computer vision: the problems and techniques related to three-dimensional (stereo) vision and motion. The emphasis is on using geometry to solve problems in stereo and motion, with examples from navigation and object recognition.Faugeras takes up such important problems in computer vision as projective geometry, camera calibration, edge detection, stereo vision (with many examples on real images), different kinds of representations and transformations (especially 3-D rotations), uncertainty and methods of addressing it, and object representation and recognition. His theoretical account is illustrated with the results of actual working programs.Three-Dimensional Computer Vision proposes solutions to problems arising from a specific robotics scenario in which a system must perceive and act. Moving about an unknown environment, the system has to avoid static and mobile obstacles, build models of objects and places in order to be able to recognize and locate them, and characterize its own motion and that of moving objects, by providing descriptions of the corresponding three-dimensional motions. The ideas generated, however, can be used indifferent settings, resulting in a general book on computer vision that reveals the fascinating relationship of three-dimensional geometry and the imaging process.Olivier Faugeras is Research Director of the Computer Vision and Robotics Laboratory at INRIA Sophia-Antipolis and a Professor of Applied Mathematics at the Ecole Polytechnique in Paris.