In Object Recognition through Invariant Indexing, Charles Rothwell provides a practical and accessible introduction to two-dimensional shape description using projective invariants while contrasting the various interpretations of the descriptors currently in use. He also surveys a number of new invariant descriptors for three-dimensional shapes that can be recovered from single images, showing how such measures can be used to ease the recognition of real objects by a computer. Rothwell then proceeds to describe a promising new architecture for a real recognition system. In reviewing a broad field of recognition theory, the book is unique in its deft synthesis of research and application. It will be welcomed by students and researchers in computer vision, robotics, pattern recognition, and image and signal processing.

The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.

The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.

The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.

This book proposes a new approach to handle the problem of limited training data. Common approaches to cope with this problem are to model the shape variability independently across predefined segments or to allow artificial shape variations that cannot be explained through the training data, both of which have their drawbacks. The approach presented uses a local shape prior in each element of the underlying data domain and couples all local shape priors via smoothness constraints. The book provides a sound mathematical foundation in order to embed this new shape prior formulation into the well-known variational image segmentation framework. The new segmentation approach so obtained allows accurate reconstruction of even complex object classes with only a few training shapes at hand.

This book constitutes the thoroughly refereed proceedings of the 11th International Conference, Spatial Cognition 2018, held in Tubingen, Germany, in September 2018. The 22 revised full papers presented in this book were carefully selected and reviewed from 44 submissions. They focus on the following topics: navigating in space; talking about space; agents, actions, and space; and individuals in space.

This two volume set (CCIS 901 and 902) constitutes the refereed proceedings of the 4th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2018 (originally ICYCSEE) held in Zhengzhou, China, in September 2018. The 125 revised full papers presented in these two volumes were carefully reviewed and selected from 1057 submissions. The papers cover a wide range of topics related to basic theory and techniques for data science including mathematical issues in data science, computational theory for data science, big data management and applications, data quality and data preparation, evaluation and measurement in data science, data visualization, big data mining and knowledge management, infrastructure for data science, machine learning for data science, data security and privacy, applications of data science, case study of data science, multimedia data management and analysis, data-driven scientific research, data-driven bioinformatics, data-driven healthcare, data-driven management, data-driven eGovernment, data-driven smart city/planet, data marketing and economics, social media and recommendation systems, data-driven security, data-driven business model innovation, social and/or organizational impacts of data science.

This book provides a survey of the state-of-the-art in the practical implementation of Spoken Dialog Systems for applications in everyday settings. It includes contributions on key topics in situated dialog interaction from a number of leading researchers and offers a broad spectrum of perspectives on research and development in the area. In particular, it presents applications in robotics, knowledge access and communication and covers the following topics: dialog for interacting with robots; language understanding and generation; dialog architectures and modeling; core technologies; and the analysis of human discourse and interaction. The contributions are adapted and expanded contributions from the 2014 International Workshop on Spoken Dialog Systems (IWSDS 2014), where researchers and developers from industry and academia alike met to discuss and compare their implementation experiences, analyses and empirical findings.

The 2-volume set LNCS 10850 and 10851 constitutes the refereed proceedings of the 5th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics, AVR 2018, held in Otranto, Italy, in June 2018. The 67 full papers and 26 short papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in the following topical sections: virtual reality; augmented and mixed reality; computer graphics; human-computer interaction; applications of VR/AR in medicine; and applications of VR/AR in cultural heritage; and applications of VR/AR in industry.

The 2-volume set LNCS 10850 and 10851 constitutes the refereed proceedings of the 5th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics, AVR 2018, held in Otranto, Italy, in June 2018. The 67 full papers and 26 short papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in the following topical sections: virtual reality; augmented and mixed reality; computer graphics; human-computer interaction; applications of VR/AR in medicine; and applications of VR/AR in cultural heritage; and applications of VR/AR in industry.

Physics-based animation is commonplace in animated feature films and even special effects for live-action movies. Think about a recent movie and there will be some sort of special effects such as explosions or virtual worlds. Cloth simulation is no different and is ubiquitous because most virtual characters (hopefully!) wear some sort of clothing. The focus of this book is physics-based cloth simulation. We start by providing background information and discuss a range of applications. This book provides explanations of multiple cloth simulation techniques. More specifically, we start with the most simple explicitly integrated mass-spring model and gradually work our way up to more complex and commonly used implicitly integrated continuum techniques in state-of-the-art implementations. We give an intuitive explanation of the techniques and give additional information on how to efficiently implement them on a computer. This book discusses explicit and implicit integration schemes for cloth simulation modeled with mass-spring systems. In addition to this simple model, we explain the more advanced continuum-inspired cloth model introduced in the seminal work of Baraff and Witkin [1998]. This method is commonly used in industry. We also explain recent work by Liu et al. [2013] that provides a technique to obtain fast simulations. In addition to these simulation approaches, we discuss how cloth simulations can be art directed for stylized animations based on the work of Wojan et al. [2016]. Controllability is an essential component of a feature animation film production pipeline. We conclude by pointing the reader to more advanced techniques.

This book covers dynamic simulation of deformable objects, which is one of the most challenging tasks in computer graphics and visualization. It focuses on the simulation of deformable models with anisotropic materials, one of the less common approaches in the existing research. Both physically-based and geometrically-based approaches are examined. The authors start with transversely isotropic materials for the simulation of deformable objects with fibrous structures. Next, they introduce a fiber-field incorporated corotational finite element model (CLFEM) that works directly with a constitutive model of transversely isotropic material. A smooth fiber-field is used to establish the local frames for each element. To introduce deformation simulation for orthotropic materials, an orthotropic deformation controlling frame-field is conceptualized and a frame construction tool is developed for users to define the desired material properties. The orthotropic frame-field is coupled with the CLFEM model to complete an orthotropic deformable model. Finally, the authors present an integrated real-time system for animation of skeletal characters with anisotropic tissues. To solve the problems of volume distortion and high computational costs, a strain-based PBD framework for skeletal animation is explained; natural secondary motion of soft tissues is another benefit. The book is written for those researchers who would like to develop their own algorithms. The key mathematical and computational concepts are presented together with illustrations and working examples. It can also be used as a reference book for graduate students and senior undergraduates in the areas of computer graphics, computer animation, and virtual reality. Academics, researchers, and professionals will find this to be an exceptional resource.

The book focuses on original approaches intended to support the development of biologically inspired cognitive architectures. It bridges together different disciplines, from classical artificial intelligence to linguistics, from neuro- and social sciences to design and creativity, among others. The chapters, based on contributions presented at the Ninth Annual Meeting of the BICA Society, held in on August 23-24, 2018, in Prague, Czech Republic, discuss emerging methods, theories and ideas towards the realization of general-purpose humanlike artificial intelligence or fostering a better understanding of the ways the human mind works. All in all, the book provides engineers, mathematicians, psychologists, computer scientists and other experts with a timely snapshot of recent research and a source of inspiration for future developments in the broadly intended areas of artificial intelligence and biological inspiration.

This book explains efficient solutions for segmenting the intensity levels of different types of multilevel images. The authors present hybrid soft computing techniques, which have advantages over conventional soft computing solutions as they incorporate data heterogeneity into the clustering/segmentation procedures. This is a useful introduction and reference for researchers and graduate students of computer science and electronics engineering, particularly in the domains of image processing and computational intelligence.

This book proposes soft computing techniques for segmenting real-life images in applications such as image processing, image mining, video surveillance, and intelligent transportation systems. The book suggests hybrids deriving from three main approaches: fuzzy systems, primarily used for handling real-life problems that involve uncertainty; artificial neural networks, usually applied for machine cognition, learning, and recognition; and evolutionary computation, mainly used for search, exploration, efficient exploitation of contextual information, and optimization. The contributed chapters discuss both the strengths and the weaknesses of the approaches, and the book will be valuable for researchers and graduate students in the domains of image processing and computational intelligence.

This comprehensive and richly illustrated volume provides up-to-date material on Singular Spectrum Analysis (SSA). SSA is a well-known methodology for the analysis and forecasting of time series. Since quite recently, SSA is also being used to analyze digital images and other objects that are not necessarily of planar or rectangular form and may contain gaps. SSA is multi-purpose and naturally combines both model-free and parametric techniques, which makes it a very special and attractive methodology for solving a wide range of problems arising in diverse areas, most notably those associated with time series and digital images. An effective, comfortable and accessible implementation of SSA is provided by the R-package Rssa, which is available from CRAN and reviewed in this book. Written by prominent statisticians who have extensive experience with SSA, the book (a) presents the up-to-date SSA methodology, including multidimensional extensions, in language accessible to a large circle of users, (b) combines different versions of SSA into a single tool, (c) shows the diverse tasks that SSA can be used for, (d) formally describes the main SSA methods and algorithms, and (e) provides tutorials on the Rssa package and the use of SSA. The book offers a valuable resource for a very wide readership, including professional statisticians, specialists in signal and image processing, as well as specialists in numerous applied disciplines interested in using statistical methods for time series analysis, forecasting, signal and image processing. The book is written on a level accessible to a broad audience and includes a wealth of examples; hence it can also be used as a textbook for undergraduate and postgraduate courses on time series analysis and signal processing.

This book proposes a semi-discrete version of the theory of Petitot and Citti-Sarti, leading to a left-invariant structure over the group SE(2,N), restricted to a finite number of rotations. This apparently very simple group is in fact quite atypical: it is maximally almost periodic, which leads to much simpler harmonic analysis compared to SE(2). Based upon this semi-discrete model, the authors improve on previous image-reconstruction algorithms and develop a pattern-recognition theory that also leads to very efficient algorithms in practice.

This volume comprises a selection of works presented at the Numerical and Evolutionary Optimization (NEO) workshop held in September 2015 in Tijuana, Mexico. The development of powerful search and optimization techniques is of great importance in today's world that requires researchers and practitioners to tackle a growing number of challenging real-world problems. In particular, there are two well-established and widely known fields that are commonly applied in this area: (i) traditional numerical optimization techniques and (ii) comparatively recent bio-inspired heuristics. Both paradigms have their unique strengths and weaknesses, allowing them to solve some challenging problems while still failing in others. The goal of the NEO workshop series is to bring together people from these and related fields to discuss, compare and merge their complimentary perspectives in order to develop fast and reliable hybrid methods that maximize the strengths and minimize the weaknesses of the underlying paradigms. Through this effort, we believe that the NEO can promote the development of new techniques that are applicable to a broader class of problems. Moreover, NEO fosters the understanding and adequate treatment of real-world problems particularly in emerging fields that affect us all such as health care, smart cities, big data, among many others. The extended papers the NEO 2015 that comprise this book make a contribution to this goal.

This book presents a unique guide to heritage preservation problems and the corresponding state-of-the-art digital techniques to achieve their plausible solutions. It covers various methods, ranging from data acquisition and digital imaging to computational methods for reconstructing the original (pre-damaged) appearance of heritage artefacts.The case studies presented here are mostly drawn from India's tangible and non-tangible heritage, which is very rich and multi-dimensional. The contributing authors have been working in their respective fields for years and present their methods so lucidly that they can be easily reproduced and implemented by general practitioners of heritage curation. The preservation methods, reconstruction methods, and corresponding results are all illustrated with a wealth of colour figures and images.The book consists of sixteen chapters that are divided into five broad sections, namely (i) Digital System for Heritage Preservation, (ii) Signal and Image Processing, (iii) Audio and Video Processing, (iv) Image and Video Database, and (v) Architectural Modelling and Visualization. The first section presents various state-of-the-art tools and technologies for data acquisition including an interactive graphical user interface (GUI) annotation tool and a specialized imaging system for generating the realistic visual forms of the artefacts. Numerous useful methods and algorithms for processing vocal, visual and tactile signals related to heritage preservation are presented in the second and third sections. In turn, the fourth section provides two important image and video databases, catering to members of the computer vision community with an interest in the domain of digital heritage. Finally, examples of reconstructing ruined monuments on the basis of historic documents are presented in the fifth section. In essence, this book offers a pragmatic appraisal of the uses of digital technology in the various aspects of preservation of tangible and intangible heritages.

The three-volume set CCIS 850, CCIS 851, and CCIS 852 contains the extended abstracts of the posters presented during the 20th International Conference on Human-Computer Interaction, HCI 2018, which took place in Las Vegas, Nevada, in July 2018. The total of 1171 papers and 160 posters included in the 30 HCII 2018 proceedings volumes was carefully reviewed and selected from 4346 submissions. The 207 papers presented in these three volumes are organized in topical sections as follows: Part I: interaction and information; images and visualizations; design, usability and user experience; psychological, cognitive and neurocognitive issues in HCI; social media and analytics. Part II: design for all, assistive and rehabilitation technologies; aging and HCI; virtual and augmented reality; emotions, anxiety, stress and well-being. Part III: learning and interaction; interacting with cultural heritage; HCI in commerce and business; interacting and driving; smart cities and smart environments. The chapter 'Information at Hand - Using Wearable Devices to Display Task Information in the Context of Industry 4.0' is open access under a CC BY 4.0 license via link.springer.com.

The three-volume set CCIS 850, CCIS 851, and CCIS 852 contains the extended abstracts of the posters presented during the 20th International Conference on Human-Computer Interaction, HCI 2018, which took place in Las Vegas, Nevada, in July 2018. The total of 1171 papers and 160 posters included in the 30 HCII 2018 proceedings volumes was carefully reviewed and selected from 4346 submissions. The 207 papers presented in these three volumes are organized in topical sections as follows: Part I: interaction and information; images and visualizations; design, usability and user experience; psychological, cognitive and neurocognitive issues in HCI; social media and analytics. Part II: design for all, assistive and rehabilitation technologies; aging and HCI; virtual and augmented reality; emotions, anxiety, stress and well-being. Part III: learning and interaction; interacting with cultural heritage; HCI in commerce and business; interacting and driving; smart cities and smart environments.

This book provides a comprehensive overview of the field of pattern mining with evolutionary algorithms. To do so, it covers formal definitions about patterns, patterns mining, type of patterns and the usefulness of patterns in the knowledge discovery process. As it is described within the book, the discovery process suffers from both high runtime and memory requirements, especially when high dimensional datasets are analyzed. To solve this issue, many pruning strategies have been developed. Nevertheless, with the growing interest in the storage of information, more and more datasets comprise such a dimensionality that the discovery of interesting patterns becomes a challenging process. In this regard, the use of evolutionary algorithms for mining pattern enables the computation capacity to be reduced, providing sufficiently good solutions. This book offers a survey on evolutionary computation with particular emphasis on genetic algorithms and genetic programming. Also included is an analysis of the set of quality measures most widely used in the field of pattern mining with evolutionary algorithms. This book serves as a review of the most important evolutionary algorithms for pattern mining. It considers the analysis of different algorithms for mining different type of patterns and relationships between patterns, such as frequent patterns, infrequent patterns, patterns defined in a continuous domain, or even positive and negative patterns. A completely new problem in the pattern mining field, mining of exceptional relationships between patterns, is discussed. In this problem the goal is to identify patterns which distribution is exceptionally different from the distribution in the complete set of data records. Finally, the book deals with the subgroup discovery task, a method to identify a subgroup of interesting patterns that is related to a dependent variable or target attribute. This subgroup of patterns satisfies two essential conditions: interpretability and interestingness.

This book introduces condition-based maintenance (CBM)/data-driven prognostics and health management (PHM) in detail, first explaining the PHM design approach from a systems engineering perspective, then summarizing and elaborating on the data-driven methodology for feature construction, as well as feature-based fault diagnosis and prognosis. The book includes a wealth of illustrations and tables to help explain the algorithms, as well as practical examples showing how to use this tool to solve situations for which analytic solutions are poorly suited. It equips readers to apply the concepts discussed in order to analyze and solve a variety of problems in PHM system design, feature construction, fault diagnosis and prognosis.

"Progress in Expressive Image Synthesis" (MEIS2015), was held in Fukuoka, Japan, September 25-27, 2015. The aim of the symposium was to provide a unique venue where various issues in computer graphics (CG) application fields could be discussed by mathematicians, CG researchers, and practitioners. Through the previous symposiums MEIS2013 and MEIS2014, mathematicians as well as CG researchers have recognized that CG is a specific and practical activity derived from mathematical theories. Issues found in CG broaden the field of mathematics and vice versa, and CG visualizes mathematical theories in an aesthetic manner. In this volume, the editors aim to provoke interdisciplinary research projects through the peer-reviewed papers and poster presentations at the this year's symposium. This book captures interactions among mathematicians, CG researchers, and practitioners sharing important, state-of-the-art issues in graphics and visual perception. The book is suitable for all CG researchers seeking open problem areas and especially for those entering the field who have not yet selected a research direction.

This book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated.