This book contains the proceedings of the workshop Uncertainty in Geomet ric Computations that was held in Sheffield, England, July 5-6, 2001. A total of 59 delegates from 5 countries in Europe, North America and Asia attended the workshop. The workshop provided a forum for the discussion of com putational methods for quantifying, representing and assessing the effects of uncertainty in geometric computations. It was organised around lectures by invited speakers, and presentations in poster form from participants. Computer simulations and modelling are used frequently in science and engi neering, in applications ranging from the understanding of natural and artificial phenomena, to the design, test and manufacturing stages of production. This widespread use necessarily implies that detailed knowledge of the limitations of computer simulations is required. In particular, the usefulness of a computer simulation is directly dependent on the user's knowledge of the uncertainty in the simulation. Although an understanding of the phenomena being modelled is an important requirement of a good computer simulation, the model will be plagued by deficiencies if the errors and uncertainties in it are not consid ered when the results are analysed. The applications of computer modelling are large and diverse, but the workshop focussed on the management of un certainty in three areas : Geometric modelling, computer vision, and computer graphics.

In June 1998 the Fourth International Workshop on Digital Mammography was held in Nijmegen, The Netherlands, where it was hosted by the department of Radiology of the University Hospital Nijmegen. This series of meetings was initiated at the 1993 SPIE Biomedical Image Processing Conference in San Jose, USA, where a number of sessions were entirely devoted to mammographic image analysis. At very successful subsequent workshops held in York, UK (1994) and Chicago, USA (1996), the scope of the conference was broadened, establishing a platform for presentation and discussion of new developments in digital mammog raphy. Topics that are addressed at these meetings are computer-aided diagnosis, image processing, detector development, system design, observer performance and clinical evaluation. The goal is to bring researchers from universities, breast cancer experts, and engineers together, to exchange information and present new scientific developments in this rapidly evolving field. This book contains all the scientific papers and posters presented at the work shop in Nijmegen. Contributions came from as many as 20 different countries and 190 participants attended the meeting. At a technical exhibit companies demon strated new products and work in progress. Abstracts of all papers were reviewed by members of the scientific committee. Many of the accepted papers had excellent quality, but due to limited space not all of them could be included as full papers in these proceedings. Papers that were rated high by the reviewers are included as long or short papers, others appear as extended abstracts in the last chapter.

Rapid development of remote sensing technology in recent years has greatly increased availability of high-resolution satellite image data. However, detailed analysis of such large data sets also requires innovative new techniques in image and signal processing.

This important text/reference presents a comprehensive review of image processing methods, for the analysis of land use in residential areas. Combining a theoretical framework with highly practical applications, making use of both well-known methods and cutting-edge techniques in computer vision, the book describes a system for the effective detection of single houses and streets in very high resolution.

Topics and features: with a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center; provides end-of-chapter summaries and review questions; presents a detailed review on remote sensing satellites; examines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indices; investigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic images; addresses the problem of detecting residential regions; describes a house and street network-detection subsystem; concludes with a summary of the key ideas covered in the book.

This pioneering work on automated satellite and aerial image-understanding systems will be of great interest to researchers in both remote sensing and computer vision, highlighting the benefit of interdisciplinary collaboration between the two communities. Urban planners and policy makers will also find considerable value in the proposed system."

Machine Learning: Discriminative and Generative covers the main contemporary themes and tools in machine learning ranging from Bayesian probabilistic models to discriminative support-vector machines. However, unlike previous books that only discuss these rather different approaches in isolation, it bridges the two schools of thought together within a common framework, elegantly connecting their various theories and making one common big-picture. Also, this bridge brings forth new hybrid discriminative-generative tools that combine the strengths of both camps. This book serves multiple purposes as well. The framework acts as a scientific breakthrough, fusing the areas of generative and discriminative learning and will be of interest to many researchers. However, as a conceptual breakthrough, this common framework unifies many previously unrelated tools and techniques and makes them understandable to a larger portion of the public. This gives the more practical-minded engineer, student and the industrial public an easy-access and more sensible road map into the world of machine learning. Machine Learning: Discriminative and Generative is designed for an audience composed of researchers & practitioners in industry and academia. The book is also suitable as a secondary text for graduate-level students in computer science and engineering.

This book constitutes the refereed conference proceedings of the 9th International Conference on Advances in Computer Entertainment, ACE 2012, held in Kathmandu, Nepal, in November 2012. The 10 full paper and 19 short papers presented together with 5 papers from the special track Arts and Culture and 35 extended abstracts were carefully reviewed and selected from a total of 140 submissions in all categories. The papers cover topics across a wide spectrum of disciplines including computer science, design, arts, sociology, anthropology, psychology, and marketing. Focusing on all areas related to interactive entertainment they aim at stimulating discussion in the development of new and compelling entertainment computing and interactive art concepts and applications.

Analyzing Video Sequences of Multiple Humans: Tracking, Posture Estimation and Behavior Recognition describes some computer vision-based methods that analyze video sequences of humans. More specifically, methods for tracking multiple humans in a scene, estimating postures of a human body in 3D in real-time, and recognizing a person's behavior (gestures or activities) are discussed. For the tracking algorithm, the authors developed a non-synchronous method that tracks multiple persons by exploiting a Kalman filter that is applied to multiple video sequences. For estimating postures, an algorithm is presented that locates the significant points which determine postures of a human body, in 3D in real-time. Human activities are recognized from a video sequence by the HMM (Hidden Markov Models)-based method that the authors pioneered. The effectiveness of the three methods is shown by experimental results.

Monitoring of public and private sites is increasingly becoming a very important and critical issue, especially after the recent flurry of terrorist attacks including the one on the Word Trade Center in September 2001. It is, therefore, imperative that effective multisensor surveillance systems be developed to protect the society from similar attacks in the future. The new generation of surveillance systems to be developed have a specific requirement: they must be able to automatically identify criminal and terrorist activity without sacrificing individual privacy to the extent possible. Privacy laws concerning monitoring and surveillance systems vary from country to country but, in general, they try to protect the privacy of their citizens. Monitoring and visual surveillance has numerous other applications. It can be employed to help invalids or handicapped and to monitor the activities of elderly people. It can be used to monitor large events such as sporting events, as well. Nowadays, monitoring is employ d in several different contexts including transport applications, such as monitoring of railway stations and airports, dangerous environments like nuclear facilities or traffic flows on roads and bridges. The latest generation of surveillance systems mainly rely on hybrid analog-digital, or completely digital video communications and processing methods and take advantage of the greater of flexibility offered by video processing algorithms that are capable focusing a human operator's attention on a set of interesting situations.

This book constitutes the proceedings of the 14th Pacific-Rim Conference on Multimedia, PCM 2013, held in Nanjing, China, in December 2013. The 30 revised full papers and 27 poster papers presented were carefully reviewed and selected from 153 submissions. The papers cover a wide range of topics in the area of multimedia content analysis, multimedia signal processing and communications and multimedia applications and services.

The fully automated estimation of the 6 degrees of freedom camera motion and the imaged 3D scenario using as the only input the pictures taken by the camera has been a long term aim in the computer vision community. The associated line of research has been known as Structure from Motion (SfM). An intense research effort during the latest decades has produced spectacular advances; the topic has reached a consistent state of maturity and most of its aspects are well known nowadays. 3D vision has immediate applications in many and diverse fields like robotics, videogames and augmented reality; and technological transfer is starting to be a reality. This book describes one of the first systems for sparse point-based 3D reconstruction and egomotion estimation from an image sequence; able to run in real-time at video frame rate and assuming quite weak prior knowledge about camera calibration, motion or scene. Its chapters unify the current perspectives of the robotics and computer vision communities on the 3D vision topic: As usual in robotics sensing, the explicit estimation and propagation of the uncertainty hold a central role in the sequential video processing and is shown to boost the efficiency and performance of the 3D estimation. On the other hand, some of the most relevant topics discussed in SfM by the computer vision scientists are addressed under this probabilistic filtering scheme; namely projective models, spurious rejection, model selection and self-calibration.

This book presents key machine vision techniques and algorithms, along with the associated Java source code. Special features include a complete self-contained treatment of all topics and techniques essential to the understanding and implementation of machine vision; an introduction to object-oriented programming and to the Java programming language, with particular reference to its imaging capabilities; Java source code for a wide range of real-world image processing and analysis functions; an introduction to the Java 2D imaging and Java Advanced Imaging (JAI) API; and a wide range of illustrative examples.

Fourier Vision provides a new treatment of figure-ground segmentation in scenes comprising transparent, translucent, or opaque objects. Exploiting the relative motion between figure and ground, this technique deals explicitly with the separation of additive signals and makes no assumptions about the spatial or spectral content of the images, with segmentation being carried out phasor by phasor in the Fourier domain. It works with several camera configurations, such as camera motion and short-baseline binocular stereo, and performs best on images with small velocities/displacements, typically one to ten pixels per frame. The book also addresses the use of Fourier techniques to estimate stereo disparity and optical flow. Numerous examples are provided throughout. Fourier Vision will be of value to researchers in image processing & computer vision and, especially, to those who have to deal with superimposed transparent or translucent objects. Researchers in application areas such as medical imaging and acoustic signal processing will also find this of interest.

The seven-volume set comprising LNCS volumes 7572-7578 constitutes the refereed proceedings of the 12th European Conference on Computer Vision, ECCV 2012, held in Florence, Italy, in October 2012. The 408 revised papers presented were carefully reviewed and selected from 1437 submissions. The papers are organized in topical sections on geometry, 2D and 3D shape, 3D reconstruction, visual recognition and classification, visual features and image matching, visual monitoring: action and activities, models, optimisation, learning, visual tracking and image registration, photometry: lighting and colour, and image segmentation.

Morphometrics is concerned with the study of variations and change in the form (size and shape) of organisms or objects adding a quantitative element to descriptions and thereby facilitating the comparison of different objects and organisms. This volume provides an introduction to morphometrics in a clear and simple way without recourse to complex mathematics and statistics. This introduction is followed by a series of case studies describing the variety of applications of morphometrics from paleontology and evolutionary ecology to archaeological artifacts analysis. This is followed by a presentation of future applications of morphometrics and state of the art software for analyzing and comparing shape.

The Distinguished Dissertation Series is published on behalf of the Conference of Professors and Heads of Computing and the British Computer Society, who annually select the best British PhD dissertations in computer science for publication. The dissertations are selected on behalf of the CPHC by a panel of eight academics. Each dissertation chosen makes a noteworthy contribution to the subject and reaches a high standard of exposition, placing all results clearly in the context of computer science as a whole. In this way computer scientists with significantly different interests are able to grasp the essentials - or even find a means of entry - to an unfamiliar research topic. This book investigates how information contained in multiple, overlapping images of a scene may be combined to produce images of superior quality. This offers possibilities such as noise reduction, extended field of view, blur removal, increased spatial resolution and improved dynamic range. Potential applications cover fields as diverse as forensic video restoration, remote sensing, video compression and digital video editing.The book covers two aspects that have attracted particular attention in recent years: image mosaicing, whereby multiple images are aligned to produce a large composite; and super-resolution, which permits restoration at an increased resolution of poor quality video sequences by modelling and removing imaging degradations including noise, blur and spacial-sampling. It contains a comprehensive coverage and analysis of existing techniques, and describes in detail novel, powerful and automatic algorithms (based on a robust, statistical framework) for applying mosaicing and super-resolution. The algorithms may be implemented directly from the descriptions given here. A particular feature of the techniques is that it is not necessary to know the camera parameters (such as position and focal length) in order to apply them. Throughout the book, examples are given on real image sequences, covering a variety of applications including: the separation of latent marks in forensic images; the automatic creation of 360 panoramic mosaics; and super-resolution restoration of various scenes, text, and faces in lw-quality video.

This book constitutes the thoroughly reviewed post-proceedings of the 8th International Workshop on Argumentation in Multi-Agent Systems, ArgMas 2011, held in Taipei, Taiwan in May 2011 in association with the 10th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2011). The 8 revised full papers taken from ArgMAS 2011. Also included are 5 invited papers based on presentations on argumentation at the AAMAS 2011 main conference. All together the 13 papers included in the book give a representative overview on current research on argumentation in multi-agent systems. The papers are listed alphabetically by first author within three thematic topics: foundations and theory; argumentation and dialogue; and applications.

The seven-volume set comprising LNCS volumes 7572-7578 constitutes the refereed proceedings of the 12th European Conference on Computer Vision, ECCV 2012, held in Florence, Italy, in October 2012. The 408 revised papers presented were carefully reviewed and selected from 1437 submissions. The papers are organized in topical sections on geometry, 2D and 3D shapes, 3D reconstruction, visual recognition and classification, visual features and image matching, visual monitoring: action and activities, models, optimisation, learning, visual tracking and image registration, photometry: lighting and colour, and image segmentation.

Intelligent Unmanned Ground Vehicles describes the technology developed and the results obtained by the Carnegie Mellon Robotics Institute in the course of the DARPA Unmanned Ground Vehicle (UGV) project. The goal of this work was to equip off-road vehicles with computer-controlled, unmanned driving capabilities. The book describes contributions in the area of mobility for UGVs including: tools for assembling complex autonomous mobility systems; on-road and off-road navigation; sensing techniques; and route planning algorithms. In addition to basic mobility technology, the book covers a number of integrated systems demonstrated in the field in realistic scenarios. The approaches presented in this book can be applied to a wide range of mobile robotics applications, from automated passenger cars to planetary exploration, and construction and agricultural machines. Intelligent Unmanned Ground Vehicles shows the progress that was achieved during this program, from brittle specially-built robots operating under highly constrained conditions, to groups of modified commercial vehicles operating in tough environments. One measure of progress is how much of this technology is being used in other applications. For example, much of the work in road-following, architectures and obstacle detection has been the basis for the Automated Highway Systems (AHS) prototypes currently under development. AHS will lead to commercial prototypes within a few years. The cross-country technology is also being used in the development of planetary rovers with a projected launch date within a few years. The architectural tools built under this program have been used in numerous applications, from an automated harvester to an autonomous excavator. The results reported in this work provide tools for further research development leading to practical, reliable and economical mobile robots.

The seven-volume set comprising LNCS volumes 7572-7578 constitutes the refereed proceedings of the 12th European Conference on Computer Vision, ECCV 2012, held in Florence, Italy, in October 2012. The 408 revised papers presented were carefully reviewed and selected from 1437 submissions. The papers are organized in topical sections on geometry, 2D and 3D shapes, 3D reconstruction, visual recognition and classification, visual features and image matching, visual monitoring: action and activities, models, optimisation, learning, visual tracking and image registration, photometry: lighting and colour, and image segmentation.

This monograph is a revised version of the D.Phil. thesis of the first author, submitted in October 1990 to the University of Oxford. This work investigates the problem of mobile robot navigation using sonar. We view model-based navigation as a process of tracking naturally occurring environment features, which we refer to as "targets". Targets that have been predicted from the environment map are tracked to provide that are observed, but not predicted, vehicle position estimates. Targets represent unknown environment features or obstacles, and cause new tracks to be initiated, classified, and ultimately integrated into the map. Chapter 1 presents a brief definition of the problem and a discussion of the basic research issues involved. No attempt is made to survey ex haustively the mobile robot navigation literature-the reader is strongly encouraged to consult other sources. The recent collection edited by Cox and Wilfong [34] is an excellent starting point, as it contains many of the standard works of the field. Also, we assume familiarity with the Kalman filter. There are many well-known texts on the subject; our notation derives from Bar-Shalom and Fortmann [7]. Chapter 2 provides a detailed sonar sensor model. A good sensor model of our approach to navigation, and is used both for is a crucial component predicting expected observations and classifying unexpected observations.

Dynamic Neural Field Theory for Motion Perception provides a new theoretical framework that permits a systematic analysis of the dynamic properties of motion perception. This framework uses dynamic neural fields as a key mathematical concept. The author demonstrates how neural fields can be applied for the analysis of perceptual phenomena and its underlying neural processes. Also, similar principles form a basis for the design of computer vision systems as well as the design of artificially behaving systems. The book discusses in detail the application of this theoretical approach to motion perception and will be of great interest to researchers in vision science, psychophysics, and biological visual systems.

This book constitutes the refereed proceedings of the International Workshop on Augemented Environments for Computer-Assited Interventions, held in conjunction with MICCAI 2011, in Toronto, Canada, in September 2011. The 13 revised full papers presented were carefully reviewed and selected from 21 submissions. The papers cover the following topics: image registration and fusion, calibration, visualisation and 3D perception, hardware and optical design, real-time implementations, validation, clinical applications and clinical evaluation.

An Analog VLSI System for Stereoscopic Vision investigates the interaction of the physical medium and the computation in both biological and analog VLSI systems by synthesizing a functional neuromorphic system in silicon. In both the synthesis and analysis of the system, a point of view from within the system is adopted rather than that of an omniscient designer drawing a blueprint. This perspective projects the design and the designer into a living landscape. The motivation for a machine-centered perspective is explained in the first chapter. The second chapter describes the evolution of the silicon retina. The retina accurately encodes visual information over orders of magnitude of ambient illumination, using mismatched components that are calibrated as part of the encoding process. The visual abstraction created by the retina is suitable for transmission through a limited bandwidth channel. The third chapter introduces a general method for interchip communication, the address-event representation, which is used for transmission of retinal data. The address-event representation takes advantage of the speed of CMOS relative to biological neurons to preserve the information of biological action potentials using digital circuitry in place of axons. The fourth chapter describes a collective circuit that computes stereodisparity. In this circuit, the processing that corrects for imperfections in the hardware compensates for inherent ambiguity in the environment. The fifth chapter demonstrates a primitive working stereovision system. An Analog VLSI System for Stereoscopic Vision contributes to both computer engineering and neuroscience at a concrete level. Through the construction of a working analog of biological vision subsystems, new circuits for building brain-style analog computers have been developed. Specific neuropysiological and psychophysical results in terms of underlying electronic mechanisms are explained. These examples demonstrate the utility of using biological principles for building brain-style computers and the significance of building brain-style computers for understanding the nervous system.

This book constitutes the refereed proceedings of the International Conference on Computer Vision and Graphics, ICCVG 2012, held in Warsaw, Poland, in September 2012. The 89 revised full papers presented were carefully reviewed and selected from various submissions. The papers are organized in topical sections on computer graphics, computer vision and visual surveillance.

Although there has been much progress in developing theories, models and systems in the areas of natural language processing (NLP) and vision processing (VP), there has hitherto been little progress in integrating these two subareas of artificial intelligence. The papers in Integration of Natural Language and Vision Processing focus on site descriptions, such as the work at Apple Computer, California, and the DFKI, Saarbrucken, on historical surveys and philosophical issues, on systems that have been built, enabling communication through text, speech, sound, touch, video, graphics and icons, and on the automatic presentation of information, whether it be in the form of instruction manuals, statistical data or visualisation of language. There is also a review of Mark Maybury's book Intelligent Multimedia Interfaces. Audience: Vital reading for all interested in the SuperInformationHighways of the future.

Measurement of Image Velocity presents a computational framework for computing motion information from sequences of images. Its specific goal is the measurement of image velocity (or optical flow), the projection of 3-D object motion onto the 2-D image plane. The formulation of the problem emphasizes the geometric and photometric properties of image formation, and the occurrence of multiple image velocities caused, for example, by specular reflections, shadows, or transparency. The method proposed for measuring image velocity is based on the phase behavior in the output of velocity-tuned filters. Extensive experimental work is used to show that phase can be a reliable source of pure image translation, small geometric deformation, smooth contrast variations, and multiple local velocities. Extensive theorectical analysis is used to explain the robustness of phase with respect to deviations from image translation, and to detect situations in which phase becomes unstable. The results indicate that optical flow may be extracted reliably for computing egomotion and structure from motion. The monograph also contains a review of other techniques and frequency analysis applied to image sequences, and it discusses the closely related topics of zero-crossing tracking, gradient-based methods, and the measurement of binocular disparity. The work is relevant to those studying machine vision and visual perception.