In recent years there has been an increasing interest in Second Generation Image and Video Coding Techniques. These techniques introduce new concepts from image analysis that greatly improve the performance of the coding schemes for very high compression. This interest has been further emphasized by the future MPEG 4 standard. Second generation image and video coding techniques are the ensemble of approaches proposing new and more efficient image representations than the conventional canonical form. As a consequence, the human visual system becomes a fundamental part of the encoding/decoding chain. More insight to distinguish between first and second generation can be gained if it is noticed that image and video coding is basically carried out in two steps. First, image data are converted into a sequence of messages and, second, code words are assigned to the messages. Methods of the first generation put the emphasis on the second step, whereas methods of the second generation put it on the first step and use available results for the second step. As a result of including the human visual system, second generation can be also seen as an approach of seeing the image composed by different entities called objects. This implies that the image or sequence of images have first to be analyzed and/or segmented in order to find the entities. It is in this context that we have selected in this book three main approaches as second generation video coding techniques: Segmentation-based schemes Model Based Schemes Fractal Based Schemes GBP/LISTGBP Video Coding: The Second Generation Approach is an important introduction to the new coding techniques for video. As such, all researchers, students and practitioners working in image processing will find this book of interest.

Visual languages have long been lit pursuitofeffective communication 00 tween human and machine. Today, they are suecessfully employed for e: nd user progmmming, modeliog, rapid prototypmg, and design activities by people ofmany disciplines including arehitects, artists, children, engi neers, and scientists. Furthermore. with rapid advances ofthe Internet and Web technology, human human communication through the Web or eleo tronie mobile deviees is becoming more and moreprevalent This manuscript provides a comprehensive introduetion to diagmmmatiooI visual programming languages and the technologyofautomatie genemtion ofsnch languages. It covers a broad rangeofcontents from the underlying theoryofgraph grammars to the applications in various domains. Thecon tents were ex: l: l: aeted from the papers that my Ph. D. students and I have published in the last 10 years. and are updated and organized in a coherent fashion. The manuseript gives an in. -depth treatmentof all the topic areas. Pointers to related work and further readings are also faeilitated at the end ofeverychapterexeeptChapter 9. Rather than describing how to program visually, the manuscript discusses what are visual programming languages, and how sooh languages and their underlying foundations can be usefully applied to other fields incomputer science that need graphs as the p: rimary meansofrepresentation. Assuming the basic knowledge of computer programming and compiler co: nstruetion, the manuscript can be used as a textbook for senior orgradu ate computer science classes on visual languages, or a reference book for programming language classes, practitioners, and researchers inthe related field. The manuscript cannot be completed without the helps of many people.

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 up to now been little progress on integrating these two subareas of Artificial Intelligence (AI). This book contains a set of edited papers on recent advances in the theories, computational models and systems of the integration of NLP and VP. The volume includes original work of notable researchers: Alex Waibel outlines multimodal interfaces including studies in speech, gesture and points; eye-gaze, lip motion and facial expression; hand writing, face recognition, face tracking and sound localization in a connectionist framework. Antony Cohen and John Gooday use spatial relations to describe visual languages. Naoguki Okada considers intentions of agents in visual environments. In addition to these studies, the volume includes many recent advances from North America, Europe and Asia demonstrating the fact that integration of Natural Language Processing and Vision is truly an international challenge.

COMPUTER VISION is a field of research that encompasses many objectives. A primary goal has been to construct visual sensors that can provide general-purpose robots with the same information about their surroundings as we receive from our own visual senses. This book takes an important step towards this goal by describing a working computer vision system named SCERPO. This system can recognize known three-dimensional objects in ordinary black-and-white images taken from unknown viewpoints, even when parts of the object are undetectable or hidden from view. A second major goal of computer vision re search is to provide a computational understanding of human vision. The research presented in this book has many implica tions for our understanding of human vision, particularly in the areas of perceptual organization and knowledge-based recogni tion. An attempt has been made to relate each computational result to the relevant areas in the psychology of vision. Since the material is meant to be accessible to a wide range of inter disciplinary readers, the book is written in plain language and attempts to explain most concepts from the starting position of the non-specialist. vii viii PREFACE One of the most important conclusions ansmg from this research is that visual recognition can commonly be achieved directly from the two-dimensional image without any prelim inary reconstruction of depth information or surface orienta tion from the visual input."

Arobotmustperceivethethree-dimensionalworldifitistobeeffective there. Yet recovering 3-D information from projected images is difficult, and still remains thesubjectofbasic research. Alternatively, onecan use sensorsthatcanprovidethree-dimensionalrangeinformationdirectly. The technique ofprojecting light-stripesstartedto be used in industrialobject recognition systems asearly asthe 1970s,andtime-of-flight laser-scanning range finders became available for outdoor mobile robotnavigation in the mid-eighties. Once range data are obtained, a vision system must still describe the scene in terms of 3-D primitives such as edges, surfaces, and volumes, and recognize objeCts of interest. Today, the art of sensing, extractingfeatures, and recognizing objectsbymeans ofthree-dimensional rangedataisoneofthemostexcitingresearchareasincomputervision. Three-Dimensional Machine Vision is a collection of papers dealing withthree-dimensionalrangedata. Theauthorsarepioneeringresearchers: some are founders and others are bringingnew excitements in thefield. I have tried to select milestone papers, and my goalhas beento make this bookareferenceworkforresearchersinthree-dimensionalvision. The book is organized into four parts: 3-D Sensors, 3-D Feature Extractions,ObjectRecognitionAlgorithms,andSystemsandApplications. Part I includes four papers which describe the development of unique, capable 3-D range sensors, as well as discussions of optical, geometrical, electronic, and computational issues. Mundy and Porter describe asensor systembasedonstructuredilluminationforinspectingmetalliccastings. In order to achieve high-speed data acquisition, it uses multiple lightstripes withwavelength multiplexing. Case, Jalkio,andKim alsopresentamulti- stripe system and discuss various design issues in range sensing by triangulation. ThenumericalstereocameradevelopedbyAltschuler, Bae, Altschuler, Dijak, Tamburino, and Woolford projects space-coded grid patterns which are generated by an electro-optical programmable spatial viii PREFACE light modulator. Kanade and Fuhrman present a proximity sensor using multipleLEDswhich areconically arranged. Itcan measurebothdistance andorientationofanobject'ssurface.

CHAPTER 7: MATCHING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 7. 1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 7. 2 Design of the matcher . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 7. 3 Model instantiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 7. 3. 1 Discrimination by size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 7. 3. 2 Discrimination by gross shape . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 7. 3. 3 Feature attribute matching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 7. 3. 4 Surface attribute matching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 7. 3. 5 Classifying surfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 7. 3. 6 Relational consistency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 7. 3. 7 Ordering matches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 7. 4 Verification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 7. 4. 1 Computing model-to-scene transformations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 7. 4. 2 Matching feature frames . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 7. 4. 3 Matching surface frames. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 7. 4. 4 Verification sensing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 7. 5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 CHAPTER 8: EXPERIMENTAL RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 8. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 8. 2 Experiment 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 8. 3 Experiment 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 8. 4 Experiment 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 8. 5 Experiment 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 8. 6 Experiment 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 8. 7 Experiment 6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 8. 8 Experiment 7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138 8. 9 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 CHAPTER 9: CONCLUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 9. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 9. 2 Discovering 3-D structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 9. 3 The multi-sensor approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 9. 4 Limitations of the system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 9. 5 Future directions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 - viii - APPENDIX: BICUBIC SPLINE SURFACES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 2. Parametric curves and surfaces. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 3. Coons' patches. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 3. 1 Linearly interpolated patches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 3. 2 Hermite interpolation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 3. 3 Curvature continuous patches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 INDEX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Augmented (AR) and Virtual Reality (VR) technologies are increasingly being used in manufacturing processes. These use real and simulated objects to create a simulated environment that can be used to enhance the design and manufacturing processes.

Virtual Reality and Augmented Reality Applications in Manufacturing is written by experts from the world s leading institutions working in virtual manufacturing and gives the state of the art of the field.

Features:

- Chapters covering the state of the art in VR and AR technology and how these technologies can be applied to manufacturing.

- The latest findings in key areas of AR and VR application to manufacturing.

- The results of recent cross-disciplinary research projects in the US and Europe showing application solutions of AR and VR technology in real industrial settings.

Virtual Reality and Augmented Reality Applications in Manufacturing will be of interest to all engineers wishing to keep up-to-date with technologies that have the potential to revolutionize manufacturing processes over the next few years."

A central problem in computer vision is to track objects as they move and deform in a video sequence. Stochastic algorithms -- in particular, particle filters and the Condensation algorithm -- have dramatically enhanced the state of the art for such visual tracking problems in recent years. This book presents a unified framework for visual tracking using particle filters, including the new technique of partitioned sampling which can alleviate the "curse of dimensionality" suffered by standard particle filters. The book also introduces the notion of contour likelihood: a collection of models for assessing object shape, colour and motion, which are derived from the statistical properties of image features. Because of their statistical nature, contour likelihoods are ideal for use in stochastic algorithms. A unifying theme of the book is the use of statistics and probability, which enable the final output of the algorithms presented to be interpreted as the computer's "belief" about the state of the world. The book will be of use and interest to students, researchers and practitioners in computer vision, and assumes only an elementary knowledge of probability theory.

The book is about Gentzen calculi for (the main systems of) modal logic. It is divided into three parts. In the first partwe introduce and discuss the main philosophical ideas related to proof theory, and we try to identify criteria for distinguishing good sequent calculi. In the second part we present the several attempts made from the 50's until today to provide modal logic with Gentzen calculi. In the third and and final part we analyse new calculi for modal logics, called tree-hypersequent calculi, which were recently introduced by the author. We show in a precise and clear way the main results that can be proved with and about them.

"

This book constitutes the refereed proceedings of the Second International Workshop on Machine Learning in Medical Imaging, MLMI 2011, held in conjunction with MICCAI 2011, in Toronto, Canada, in September 2011. The 44 revised full papers presented were carefully reviewed and selected from 74 submissions. The papers focus on major trends in machine learning in medical imaging aiming to identify new cutting-edge techniques and their use in medical imaging.

This book contains the proceedings of the 4th International Conference on Data Analysis and Processing held in Cefalu' (Palermo, ITALY) on September 23-25 1987. The aim of this Conference, now at its fourth edition, was to give a general view of the actual research in the area of methods and systems for achieving artificial vision as well as to have an up-dated information of the current activity in Europe. A number of invited speakers presented overviews of statistical classification problems and methods, non conventional archi tectures, mathematical morphology, robotic vision, analysis of range images in vision systems, pattern matching algorithms and astronomical data processing. Finally a survey of the discussion on the contribution of AI to Image Analysis is given. The papers presented at the Conference have been subdivided in four sections: knowledge based approaches, basic pattern recognition tools, multi features system based solutions, image analysis-applications. We must thank the IBM-Italia and the Digital Equipment Corpo ration for sponsoring this Conference. We feel that the days spent at Cefalu' were an important step toward the mutual exchange of scientific information within the image processing community. v. Cantoni Pavia University V. Di Gesu' Palermo University S. Levialdi Rome University v CONTENTS INVITED LECTURES . * * * * . * * * 3 Morphological Optics.

Matrix transforms are ubiquitous within the world of computer graphics, where they have become an invaluable tool in a programmer's toolkit for solving everything from 2D image scaling to 3D rotation about an arbitrary axis. Virtually every software system and hardware graphics processor uses matrices to undertake operations such as scaling, translation, reflection and rotation. Nevertheless, for some newcomers to the world of computer games and animation, matrix notation can appear obscure and challenging.

Matrices and determinants were originally used to solve groups of simultaneous linear equations, and were subsequently embraced by the computer graphics community to describe the geometric operations for manipulating two- and three-dimensional structures. Consequently, to place matrix notation within an historical context, the author provides readers with some useful background to their development, alongside determinants.

Although it is assumed that the reader is familiar with everyday algebra and the solution of simultaneous linear equations, "Matrix Transforms for Computer Games and Animation" does not expect any prior knowledge of matrix notation. It includes chapters on matrix notation, determinants, matrices, 2D transforms, 3D transforms and quaternions, and includes many worked examples to illustrate their practical use.

Vision has to deal with uncertainty. The sensors are noisy, the prior knowledge is uncertain or inaccurate, and the problems of recovering scene information from images are often ill-posed or underconstrained. This research monograph, which is based on Richard Szeliski's Ph.D. dissertation at Carnegie Mellon University, presents a Bayesian model for representing and processing uncertainty in low level vision. Recently, probabilistic models have been proposed and used in vision. Sze liski's method has a few distinguishing features that make this monograph im portant and attractive. First, he presents a systematic Bayesian probabilistic estimation framework in which we can define and compute the prior model, the sensor model, and the posterior model. Second, his method represents and computes explicitly not only the best estimates but also the level of uncertainty of those estimates using second order statistics, i.e., the variance and covariance. Third, the algorithms developed are computationally tractable for dense fields, such as depth maps constructed from stereo or range finder data, rather than just sparse data sets. Finally, Szeliski demonstrates successful applications of the method to several real world problems, including the generation of fractal surfaces, motion estimation without correspondence using sparse range data, and incremental depth from motion."

This book constitutes the refereed proceedings of the First International Conference on Information and Communication Technology for the Fight against Global Warming, ICT-Glow 2011, held in Toulouse, France in August 2011. The 16 revised papers presented were carefully reviewed and selected from 24 submissions. They address the following topics: parallel computing, ICT for transportation, cloud and pervasive computing, measurement and control and storage.

As cameras become more pervasive in our daily life, vast amounts of video data are generated. The popularity of YouTube and similar websites such as Tudou and Youku provides strong evidence for the increasing role of video in society. One of the main challenges confronting us in the era of information technology is to - fectively rely on the huge and rapidly growing video data accumulating in large multimedia archives. Innovative video processing and analysis techniques will play an increasingly important role in resolving the difficult task of video search and retrieval. A wide range of video-based applications have benefited from - vances in video search and mining including multimedia information mana- ment, human-computer interaction, security and surveillance, copyright prot- tion, and personal entertainment, to name a few. This book provides an overview of emerging new approaches to video search and mining based on promising methods being developed in the computer vision and image analysis community. Video search and mining is a rapidly evolving discipline whose aim is to capture interesting patterns in video data. It has become one of the core areas in the data mining research community. In comparison to other types of data mining (e. g. text), video mining is still in its infancy. Many challenging research problems are facing video mining researchers.

Efficient transfer between science and society is crucial for their future development. The rapid progress of information technology and computer systems offers a large potential and new perspectives for solving complex problems. Mathematical modelling and simulation have become important tools not only in scientific investigations but also in analysing, planning and controlling technological and economic processes. Mathematics, imbedded in an interdisciplinary concept, has become a key technology.

The book covers the results of a variety of major projects in industrial mathematics following an initiative of the German Federal Ministry of Education and Research. All projects are collaborations of industrial companies and university-based researchers, and range from automotive industry to computer technology and medical visualisation. In general, the projects presented in this volume prove that new mathematical ideas and methods can be decisive for the solution of industrial and economic problems.

The five volume set CCIS 224-228 constitutes the refereed proceedings of the International conference on Applied Informatics and Communication, ICAIC 2011, held in Xi'an, China in August 2011.

The 446 revised papers presented were carefully reviewed and selected from numerous submissions. The papers cover a broad range of topics in computer science and interdisciplinary applications including control, hardware and software systems, neural computing, wireless networks, information systems, and image processing.

This book constitutes the refereed conference proceedings of the 20th International Workshop on Functional and Constraint Logic Programming, WFLP 2011, held in Odense, Denmark, in July 2011 as Part of the 13th International Symposium on Principles and Practice of Declarative Programming (PPDP 2011), the 22st International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2011), and the 4th International Workshop on Approaches and Applications of Inductive Programming (AAIP 2011). From the 10 papers submitted, 9 were accepted for presentation the proceeding. The papers cover current research in all areas of functional and logic programming as well as the integration of constraint logic and object-oriented programming, and term rewriting.

A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empirical feature space, and the effect of model selection by cross-validation; Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Explores incremental training based batch training and active-set training methods, and decomposition techniques for linear programming SVMs; Discusses variable selection for support vector regressors.

This book constitutes the refereed proceedings of the 16th Australasian Conference on Information Security and Privacy, ACISP 2011, held in Melbourne, Australia, in July 2011. The 24 revised full papers presented together with an invited talk and 9 poster papers were carefully reviewed and selected from 103 submissions. The papers are organized in topical sections on symmetric key cryptography, hash functions, cryptographic protocols, access control and security, and public key cryptography.

The aim of computer-aided surgery (CAS) is to advance the utilization of computers in the development of new technologies for medical services. The Asian Conference on Computer Aided Surgery (ACCAS) series provides a forum for academic researchers, clinical scientists, surgeons, and industrial partners to exchange new ideas, techniques, and the latest developments in the field. The ACCAS brings together researchers from all fields related to medical activity visualization, simulation and modeling, virtual reality for CAS, image-guided diagnosis and therapies, CAS for minimally invasive intervention, medical robotics and instrumentation, surgical navigation, clinical application of CAS, telemedicine and telesurgery, and CAS education. The ACCAS is also interested in promoting collaboration among people from different disciplines and different countries in Asia and the world. This volume helps to achieve that goal and is a valuable resource for researchers and clinicians in the field.

The ability to extract generic 3D objects from images is a crucial step towards automation of a variety of problems in cartographic database compilation, industrial inspection and assembly, and autonomous navigation. Many of these problem domains do not have strong constraints on object shape or scene content, presenting serious obstacles for the development of robust object detection and delineation techniques. Geometric Constraints for Object Detection and Delineation addresses these problems with a suite of novel methods and techniques for detecting and delineating generic objects in images of complex scenes, and applies them to the specific task of building detection and delineation from monocular aerial imagery. PIVOT, the fully automated system implementing these techniques, is quantitatively evaluated on 83 images covering 18 test scenes, and compared to three existing systems for building extraction. The results highlight the performance improvements possible with rigorous photogrammetric camera modeling, primitive-based object representations, and geometric constraints derived from their combination. PIVOT's performance illustrates the implications of a clearly articulated set of philosophical principles, taking a significant step towards automatic detection and delineation of 3D objects in real-world environments. Geometric Constraints for Object Detection and Delineation is suitable as a textbook or as a secondary text for a graduate-level course, and as a reference for researchers and practitioners in industry.

This book constitutes the refereed proceedings of the 11th International Symposium on Smart Graphics, SG 2011, held in Bremen, Germany, in July 2011. The 10 revised full papers presented together with 12 short papers and 4 systems demonstrations were carefully reviewed and selected from numerous submissions covering a wide range of topics including view and camera control; three-dimensional modeling; visual information encoding; video projection; information visualization; interaction techniques; visual communication; and graphics and audio.

The range of applications in the area of motion analysis and image sequence processing is expanding with the steady increase in the use of video and television systems in a variety of different fields. A consequence of this expansion is the increased interest in research in this area. Motion Analysis and Image Sequence Processing brings together the fundamentals of various aspects of image sequence processing, as well as the most recent developments and applications. An image sequence is a series of two-dimensional images that are sequentially ordered in time. The analysis of image motion, and processing of image sequences using the motion information is becoming more and more important as video and television systems are finding an increasing number of applications in the areas of entertainment, robot vision, education, personal communications, multimedia, and scientific research. The importance of motion analysis and image sequence processing is due to two major factors. First, the information that needs to be obtained from the sequence may be inherently time-dependent. In that case, spatial information that can be obtained from a single image frame may not bear any useful information, and hence one must utilize temporal information by considering a sequence of images. Second, in some applications it may be advantageous to consider the processing of a sequence of images instead of individual images. This is because one can utilize the naturally existing temporal relationship among the frames of an image sequence to obtain results that are superior to those obtained by frame-by-frame processing of the sequence. Motion Analysis and Image Sequence Processing contains a coherent and rigorous discussion of recent fundamental developments, as well as applications of motion estimation and image sequence processing. Motion Analysis and Image Sequence Processing is a useful reference for engineers, industrial and academic research scientists, graduate students and faculty who are either already active in research in the field or planning to pursue research in one or more aspects of image sequence processing. This book can be used as the textbook in an advanced level course and as a reference. (ABSTRACT) The range of applications in the area of motion analysis and image sequence processing is expanding with the steady increase in the use of video and television systems in a variety of different fields. A consequence of this expansion is the increased interest in research in this area. Motion Analysis and Image Sequence Processing brings together the fundamentals of various aspects of image sequence processing, as well as the most recent developments and applications. An image sequence is a series of two-dimensional images that are sequentially ordered in time. The analysis of image motion, and processing of image sequences using the motion information is becoming more and more important as video and television systems are finding an increasing number of applications in the areas of entertainment, robot vision, education, personal communications, multimedia, and scientific research. The importance of motion analysis and image sequence processing is due to two major factors. First, the information that needs to be obtained from the sequence may be inherently time-dependent. Motion Analysis and Image Sequence Processing contains a coherent and rigorous discussion of recent fundamental developments, as well as applications of motion estimation and image sequence processing. Motion Analysis and Image Sequence Processing is a useful reference for engineers, industrial and academic research scientists, graduate students and faculty who are either already active in research in the field or planning to pursue research in one or more aspects of image sequence processing. This book can be used as the textbook in an advanced level course and as a reference.

This book constitutes the refereed proceedings of the 8th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2011, held in Munster, Germany, in May 2011.
The 34 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on graph-based representation and characterization, graph matching, classification, and querying, graph-based learning, graph-based segmentation, and applications."