This book constitutes the refereed proceedings of the 16th International Conference on Engineering Applications of Neural Networks, EANN 2015, held in Rhodes, Greece, in September 2015. The 36 revised full papers presented together with the abstracts of three invited talks and two tutorials were carefully reviewed and selected from 84 submissions. The papers are organized in topical sections on industrial-engineering applications of ANN; bioinformatics; intelligent medical modeling; life-earth sciences intelligent modeling; learning-algorithms; intelligent telecommunications modeling; fuzzy modeling; robotics and control; smart cameras; pattern recognition-facial mapping; classification; financial intelligent modeling; echo state networks.

This comprehensive and authoritative text/reference presents a unique, multidisciplinary perspective on Shape Perception in Human and Computer Vision. Rather than focusing purely on the state of the art, the book provides viewpoints from world-class researchers reflecting broadly on the issues that have shaped the field. Drawing upon many years of experience, each contributor discusses the trends followed and the progress made, in addition to identifying the major challenges that still lie ahead. Topics and features: examines each topic from a range of viewpoints, rather than promoting a specific paradigm; discusses topics on contours, shape hierarchies, shape grammars, shape priors, and 3D shape inference; reviews issues relating to surfaces, invariants, parts, multiple views, learning, simplicity, shape constancy and shape illusions; addresses concepts from the historically separate disciplines of computer vision and human vision using the same "language" and methods.

Texture accounts for an important part of the realism of simulated experiences, and it is most certainly true during tactile interaction. We usually experience roughness by running our fingers onto the explored surface. The perception of this fine texture is mediated by the vibrations generated by the encounters of the skin and the asperities of the surfaces. Reproduction of Tactual Textures presents factors that contribute to the mechanics of the interaction between a bare finger and a surface with a view to their artificial reproduction. It discusses the recording and reproduction of tactual textures, and analyses a case study of the development of a device able to record the vibratory signal from a fingertip sliding over a textured surface. The same device is then used in a reverse way to render those previously measured signals to the user's fingertip. These developments open new questions about the biomechanical properties of the skin and their relation to perception. The second half of Reproduction of Tactual Textures focuses on the implication of the dynamic parameters of the skin onto rendering performance, and it concludes with a study on the important features that are present in the vibratory signal and their relation to texture perception. This state-of-the-art volume highlights the importance of the mechanics and biomechanics during the haptic exploration of surfaces and their possible contribution to perception. Collectively, the findings reported are pertinent to many applications, including robotic perception and the design of effective virtual reality systems.

Traditional Pattern Recognition (PR) and Computer Vision (CV) technologies have mainly focused on full automation, even though full automation often proves elusive or unnatural in many applications, where the technology is expected to assist rather than replace the human agents. However, not all the problems can be automatically solved being the human interaction the only way to tackle those applications. Recently, multimodal human interaction has become an important field of increasing interest in the research community. Advanced man-machine interfaces with high cognitive capabilities are a hot research topic that aims at solving challenging problems in image and video applications. Actually, the idea of computer interactive systems was already proposed on the early stages of computer science. Nowadays, the ubiquity of image sensors together with the ever-increasing computing performance has open new and challenging opportunities for research in multimodal human interaction. This book aims to show how existing PR and CV technologies can naturally evolve using this new paradigm. The chapters of this book show different successful case studies of multimodal interactive technologies for both image and video applications. They cover a wide spectrum of applications, ranging from interactive handwriting transcriptions to human-robot interactions in real environments.

This book constitutes the refereed proceedings of the 11th Chinese Conference on Image and Graphics Technologies and Applications, IGTA 2016, held in Beijing, China in July 2016. The 27 papers presented were carefully reviewed and selected from 69 submissions. They provide a forum for sharing progresses in the areas of image processing technology; image analysis and understanding; computer vision and pattern recognition; big data mining, computer graphics and VR; as well as image technology applications.

The field of machine learning has matured to the point where many sophisticated learning approaches can be applied to practical applications. Thus it is of critical importance that researchers have the proper tools to evaluate learning approaches and understand the underlying issues. This book examines various aspects of the evaluation process with an emphasis on classification algorithms. The authors describe several techniques for classifier performance assessment, error estimation and resampling, obtaining statistical significance as well as selecting appropriate domains for evaluation. They also present a unified evaluation framework and highlight how different components of evaluation are both significantly interrelated and interdependent. The techniques presented in the book are illustrated using R and WEKA, facilitating better practical insight as well as implementation. Aimed at researchers in the theory and applications of machine learning, this book offers a solid basis for conducting performance evaluations of algorithms in practical settings.

A unified methodology for categorizing various complex objects is presented in this book. Through probability theory, novel asymptotically minimax criteria suitable for practical applications in imaging and data analysis are examined including the special cases such as the Jensen-Shannon divergence and the probabilistic neural network. An optimal approximate nearest neighbor search algorithm, which allows faster classification of databases is featured. Rough set theory, sequential analysis and granular computing are used to improve performance of the hierarchical classifiers. Practical examples in face identification (including deep neural networks), isolated commands recognition in voice control system and classification of visemes captured by the Kinect depth camera are included. This approach creates fast and accurate search procedures by using exact probability densities of applied dissimilarity measures. This book can be used as a guide for independent study and as supplementary material for a technically oriented graduate course in intelligent systems and data mining. Students and researchers interested in the theoretical and practical aspects of intelligent classification systems will find answers to: - Why conventional implementation of the naive Bayesian approach does not work well in image classification? - How to deal with insufficient performance of hierarchical classification systems? - Is it possible to prevent an exhaustive search of the nearest neighbor in a database?

This book constitutes the refereed proceedings of the 5th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2015, held in Milan, Italy, in September 2015. The 23 full papers and 6 short papers presented were carefully reviewed and selected from 40 submissions. The papers deal with the use of technologies in favor of maintaining and improving mental wellbeing. They focus on building new computing paradigms and on addressing a multitude of challenges in mental healthcare, for example in psychiatric and psychological domains with emphasis on new technologies, such as video and audio technologies and mobile and wearable computing.

This comprehensive text/reference examines in depth the synergy between multimedia content analysis, personalization, and next-generation networking. The book demonstrates how this integration can result in robust, personalized services that provide users with an improved multimedia-centric quality of experience. Each chapter offers a practical step-by-step walkthrough for a variety of concepts, components and technologies relating to the development of applications and services. Topics and features: introduces the fundamentals of social media retrieval, presenting the most important areas of research in this domain; examines the important topic of multimedia tagging in social environments, including geo-tagging; discusses issues of personalization and privacy in social media; reviews advances in encoding, compression and network architectures for the exchange of social media information; describes a range of applications related to social media.

Soft computing includes several intelligent computing paradigms, like fuzzy logic, neural networks, and bio-inspired optimization algorithms. This book describes the application of soft computing techniques to intelligent control, pattern recognition, and optimization problems. The book is organized in four main parts. The first part deals with nature-inspired optimization methods and their applications. Papers included in this part propose new models for achieving intelligent optimization in different application areas. The second part discusses hybrid intelligent systems for achieving control. Papers included in this part make use of nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for the optimal design of intelligent controllers for different kind of applications. Papers in the third part focus on intelligent techniques for pattern recognition and propose new methods to solve complex pattern recognition problems. The fourth part discusses new theoretical concepts and methods for the application of soft computing to many different areas, such as natural language processing, clustering and optimization.

It has been traditional in phonetic research to characterize monophthongs using a set of static formant frequencies, i.e., formant frequencies taken from a single time-point in the vowel or averaged over the time-course of the vowel. However, over the last twenty years a growing body of research has demonstrated that, at least for a number of dialects of North American English, vowels which are traditionally described as monophthongs often have substantial spectral change. Vowel inherent spectral change has been observed in speakers' productions, and has also been found to have a substantial effect on listeners' perception. In terms of acoustics, the traditional categorical distinction between monophthongs and diphthongs can be replaced by a gradient description of dynamic spectral patterns. This book includes chapters addressing various aspects of vowel inherent spectral change (VISC), including theoretical and experimental studies of the perceptually relevant aspects of VISC, the relationship between articulation (vocal-tract trajectories) and VISC, historical changes related VISC, cross-dialect, cross-language, and cross-age-group comparisons of VISC, the effects of VISC on second-language speech learning, and the use of VISC in forensic voice comparison.

The two-volume set LNCS 8935 and 8936 constitutes the thoroughly refereed proceedings of the 21st International Conference on Multimedia Modeling, MMM 2015, held in Sydney, Australia, in January 2015. The 49 revised regular papers, 24 poster presentations, were carefully reviewed and selected from 189 submissions. For the three special session, a total of 18 papers were accepted for MMM 2015. The three special sessions are Personal (Big) Data Modeling for Information Access and Retrieval, Social Geo-Media Analytics and Retrieval and Image or video processing, semantic analysis and understanding. In addition, 9 demonstrations and 9 video showcase papers were accepted for MMM 2015. The accepted contributions included in these two volumes represent the state-of-the-art in multimedia modeling research and cover a diverse range of topics including: Image and Video Processing, Multimedia encoding and streaming, applications of multimedia modelling and 3D and augmented reality.

This book constitutes the refereed proceedings of the First Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2015, held in Newcastle, NSW, Australia, in February 2015. The 34 revised full papers presented were carefully reviewed and selected from 63 submissions. The papers are organized in the following topical sections: philosophy and theory; game environments and methods; learning, memory and optimization; and applications and implementations.

The computer recognition systems are nowadays one of the most promising directions in artificial intelligence. This book is the most comprehensive study of this field. It contains a collection of 79 carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections: Features, learning, and classifiers Biometrics Data Stream Classification and Big Data Analytics Image processing and computer vision Medical applications Applications RGB-D perception: recent developments and applications This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be the as well researchers as students of computer science, artificial intelligence or robotics.

This book constitutes the refereed proceedings of the European Design Science Symposium, EDSS 2013 held in Dublin, Ireland, in November 2013. The 9 papers presented together with two invited papers were carefully reviewed and selected from 18 submissions. The papers deal with various topics in the design science research.

This volume features key contributions from the International Conference on Pattern Recognition Applications and Methods, (ICPRAM 2012,) held in Vilamoura, Algarve, Portugal from February 6th-8th, 2012. The conference provided a major point of collaboration between researchers, engineers and practitioners in the areas of Pattern Recognition, both from theoretical and applied perspectives, with a focus on mathematical methodologies. Contributions describe applications of pattern recognition techniques to real-world problems, interdisciplinary research, and experimental and theoretical studies which yield new insights that provide key advances in the field. This book will be suitable for scientists and researchers in optimization, numerical methods, computer science, statistics and for differential geometers and mathematical physicists.

Graph Embedding for Pattern Recognition covers theory methods, computation, and applications widely used in statistics, machine learning, image processing, and computer vision. This book presents the latest advances in graph embedding theories, such as nonlinear manifold graph, linearization method, graph based subspace analysis, L1 graph, hypergraph, undirected graph, and graph in vector spaces. Real-world applications of these theories are spanned broadly in dimensionality reduction, subspace learning, manifold learning, clustering, classification, and feature selection. A selective group of experts contribute to different chapters of this book which provides a comprehensive perspective of this field.

Pattern recognition basically deals with the recognition of patterns, shapes, objects, things in images. Document image analysis was one of the very ?rst applications of pattern recognition and even of computing. But until the 1980s, research in this ?eld was mainly dealing with text-based documents, including OCR (Optical Character Recognition) and page layout analysis. Only a few people were looking at more speci?c documents such as music sheet, bank cheques or forms. The community of graphics recognition became visible in the late 1980s. Their speci?c interest was to recognize high-level objects represented by line drawings and graphics. The speci?c pattern recognition problems they had to deal with was raster-to-graphics conversion (i.e., recognizing graphical primitives in a cluttered pixel image), text-graphics separation, and symbol recognition. The speci?c problem of symbol recognition in graphical documents has received a lot of attention. The symbols to be recognized can be musical notation, electrical symbols, architectural objects, pictograms in maps, etc. At ?rst glance, the symbol recognition problems seems to be very similar to that of character recognition; - ter all, characters are basically a subset of symbols. Therefore, the large know-how in OCR has been extensively used in graphical symbol recognition: starting with segmenting the document to extract the symbols, extracting features from the s- bols, and then recognizing them through classi?cation or matching, with respect to a training/learning set.

This volume introduces a formal representation framework for modelling and reasoning, that allows us to quantify the uncertainty inherent in the use of vague descriptions to convey information between intelligent agents. This can then be applied across a range of applications areas in automated reasoning and learning. The utility of the framework is demonstrated by applying it to problems in data analysis where the aim is to infer effective and informative models expressed as logical rules and relations involving vague concept descriptions. The author also introduces a number of learning algorithms within the framework that can be used for both classification and prediction (regression) problems. It is shown how models of this kind can be fused with qualitative background knowledge such as that provided by domain experts. The proposed algorithms will be compared with existing learning methods on a range of benchmark databases such as those from the UCI repository.

This, the 26th issue of the Transactions on Computational Science journal, is comprised of ten extended versions of selected papers from the International Conference on Cyberworlds 2014, held in Santander, Spain, in June 2014. The topics covered include areas of virtual reality, games, social networks, haptic modeling, cybersecurity, and applications in education and arts.

Style is a fundamental and ubiquitous aspect of the human experience: Everyone instantly and constantly assesses people and things according to their individual styles, academics establish careers by researching musical, artistic, or architectural styles, and entire industries maintain themselves by continuously creating and marketing new styles. Yet what exactly style is and how it works are elusive: We certainly know it when we see it, but there is no shared and clear understanding of the diverse phenomena that we call style. The Structure of Style explores this issue from a computational viewpoint, in terms of how information is represented, organized, and transformed in the production and perception of different styles. New computational techniques are now making it possible to model the role of style in the creation of and response to human artifacts-and therefore to develop software systems that directly make use of style in useful ways. Argamon, Burns, and Dubnov organize the research they have collected in this book according to the three roles that computation can play in stylistics. The first section of the book, Production, provides conceptual foundations by describing computer systems that create artifacts-musical pieces, texts, artworks-in different styles. The second section, Perception, explains methods for analyzing different styles and gleaning useful information, viewing style as a form of communication. The final section, Interaction, deals with reciprocal interaction between style producers and perceivers, in areas such as interactive media, improvised musical accompaniment, and game playing. The Structure of Style is written for researchers and practitioners in areas including information retrieval, computer art and music, digital humanities, computational linguistics, and artificial intelligence, who can all benefit from this comprehensive overview and in-depth description of current research in this active interdisciplinary field.

The two-volume set CCIS 483 and CCIS 484 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition, CCPR 2014, held in Changsha, China, in November 2014. The 112 revised full papers presented in two volumes were carefully reviewed and selected from 225 submissions. The papers are organized in topical sections on fundamentals of pattern recognition; feature extraction and classification; computer vision; image processing and analysis; video processing and analysis; biometric and action recognition; biomedical image analysis; document and speech analysis; pattern recognition applications.

Biometrics and Kansei Engineering is the first book to bring together the principles and applications of each discipline. The future of biometrics is in need of new technologies that can depend on people's emotions and the prediction of their intention to take an action. Behavioral biometrics studies the way people walk, talk, and express their emotions, and Kansei Engineering focuses on interactions between users, products/services and product psychology. They are becoming quite complementary. This book also introduces biometric applications in our environment, which further illustrates the close relationship between Biometrics and Kansei Engineering. Examples and case studies are provided throughout this book. Biometrics and Kansei Engineering is designed as a reference book for professionals working in these related fields. Advanced-level students and researchers studying computer science and engineering will find this book useful as a reference or secondary text book as well.

Recent advances in biometrics include new developments in sensors, modalities and algorithms. As new sensors are designed, newer challenges emerge in the algorithms for accurate recognition. Written for researchers, advanced students and practitioners to use as a handbook, this volume captures the very latest state-of-the-art research contributions from leading international researchers. It offers coverage of the entire gamut of topics in the field, including sensors, data acquisition, pattern-matching algorithms, and issues that impact at the system level, such as standards, security, networks, and databases

The three volume set LNCS 8834, LNCS 8835, and LNCS 8836 constitutes the proceedings of the 21st International Conference on Neural Information Processing, ICONIP 2014, held in Kuching, Malaysia, in November 2014. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The selected papers cover major topics of theoretical research, empirical study, and applications of neural information processing research. The 3 volumes represent topical sections containing articles on cognitive science, neural networks and learning systems, theory and design, applications, kernel and statistical methods, evolutionary computation and hybrid intelligent systems, signal and image processing, and special sessions intelligent systems for supporting decision, making processes, theories and applications, cognitive robotics, and learning systems for social network and web mining.