Optimization on Riemannian manifolds-the result of smooth geometry and optimization merging into one elegant modern framework-spans many areas of science and engineering, including machine learning, computer vision, signal processing, dynamical systems and scientific computing. This text introduces the differential geometry and Riemannian geometry concepts that will help applied mathematics, computer science and engineering students and researchers gain a firm mathematical grounding to use these tools confidently in their research. Its chart-last approach will prove more intuitive from an optimizer's viewpoint, and all definitions and theorems are motivated to build time-tested optimization algorithms. Starting from first principles, the text goes on to cover current research on topics including worst-case complexity and geodesic convexity. Readers will appreciate the tricks of the trade for conducting research and for numerical implementations sprinkled throughout the book.

This book constitutes the refereed proceedings of the International Conference on Computer Vision and Graphics, ICCVG 2014, held in Warsaw, Poland, in September 2014. The 81 full papers presented were carefully reviewed and selected from various submissions. They cover various important aspects of computer vision and graphics.

This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.

This book constitutes the refereed proceedings of the 16th International Conference on Speech and Computer, SPECOM 2014, held in Novi Sad, Serbia. The 56 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 100 initial submissions. It is a conference with long tradition that attracts researchers in the area of computer speech processing (recognition, synthesis, understanding etc.) and related domains (including signal processing, language and text processing, multi-modal speech processing or human-computer interaction for instance).

This book constitutes the proceedings of the International Conference on Adaptive and Intelligent Systems, ICAIS 2014, held in Bournemouth, UK, in September 2014. The 19 full papers included in these proceedings together with the abstracts of 4 invited talks, were carefully reviewed and selected from 32 submissions. The contributions are organized under the following topical sections: advances in feature selection; clustering and classification; adaptive optimization; advances in time series analysis.

This book constitutes the proceedings of the 21st International Symposium on String Processing and Information Retrieval, SPIRE 2014, held in Ouro Preto, Brazil, in October 2014. The 20 full and 6 short papers included in this volume were carefully reviewed and selected from 45 submissions. The papers focus not only on fundamental algorithms in string processing and information retrieval, but address also application areas such as computational biology, Web mining and recommender systems. They are organized in topical sections on compression, indexing, genome and related topics, sequences and strings, search, as well as on mining and recommending.

This book constitutes the refereed proceedings of the 6th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2014, held in Montreal, QC, Canada, in October 2014. The 24 revised full papers presented were carefully reviewed and selected from 37 submissions for inclusion in this volume. They cover a large range of topics in the field of learning algorithms and architectures and discussing the latest research, results, and ideas in these areas.

This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.

This book constitutes the refereed proceedings of the 13th International Conference on Parallel Problem Solving from Nature, PPSN 2013, held in Ljubljana, Slovenia, in September 2014. The total of 90 revised full papers were carefully reviewed and selected from 217 submissions. The meeting began with 7 workshops which offered an ideal opportunity to explore specific topics in evolutionary computation, bio-inspired computing and metaheuristics. PPSN XIII also included 9 tutorials. The papers are organized in topical sections on adaption, self-adaption and parameter tuning; classifier system, differential evolution and swarm intelligence; coevolution and artificial immune systems; constraint handling; dynamic and uncertain environments; estimation of distribution algorithms and metamodelling; genetic programming; multi-objective optimisation; parallel algorithms and hardware implementations; real world applications; and theory.

This is an application-oriented book includes debugged & efficient C implementations of real-world algorithms, in a variety of languages/environments, offering unique coverage of embedded image processing. covers TI technologies and applies them to an important market (important: features the C6416 DSK) Also covers the EVM should not be lost, especially the C6416 DSK, a much more recent DSP. Algorithms treated here are frequently missing from other image processing texts, in particular Chapter 6 (Wavelets), moreover, efficient fixed-point implementations of wavelet-based algorithms also treated. Provide numerous Visual Studio .NET 2003 C/C++ code, that show how to use MFC, GDI+, and the Intel IPP library to prototype image processing applications

This book constitutes the proceedings of the 25th International Conference on Algorithmic Learning Theory, ALT 2014, held in Bled, Slovenia, in October 2014, and co-located with the 17th International Conference on Discovery Science, DS 2014. The 21 papers presented in this volume were carefully reviewed and selected from 50 submissions. In addition the book contains 4 full papers summarizing the invited talks. The papers are organized in topical sections named: inductive inference; exact learning from queries; reinforcement learning; online learning and learning with bandit information; statistical learning theory; privacy, clustering, MDL, and Kolmogorov complexity.

Information theory has proved to be effective for solving many computer vision and pattern recognition (CVPR) problems (such as image matching, clustering and segmentation, saliency detection, feature selection, optimal classifier design and many others). Nowadays, researchers are widely bringing information theory elements to the CVPR arena. Among these elements there are measures (entropy, mutual information...), principles (maximum entropy, minimax entropy...) and theories (rate distortion theory, method of types...). This book explores and introduces the latter elements through an incremental complexity approach at the same time where CVPR problems are formulated and the most representative algorithms are presented. Interesting connections between information theory principles when applied to different problems are highlighted, seeking a comprehensive research roadmap. The result is a novel tool both for CVPR and machine learning researchers, and contributes to a cross-fertilization of both areas.

Throughout much of machine vision's early years the infrared imagery has suffered from return on investment despite its advantages over visual counterparts. Recently, the ?scal momentum has switched in favor of both manufacturers and practitioners of infrared technology as a result of today's rising security and safety challenges and advances in thermographic sensors and their continuous drop in costs. This yielded a great impetus in achieving ever better performance in remote surveillance, object recognition, guidance, noncontact medical measurements, and more. The purpose of this book is to draw attention to recent successful efforts made on merging computer vision applications (nonmilitary only) and nonvisual imagery, as well as to ?ll in the need in the literature for an up-to-date convenient reference on machine vision and infrared technologies. Augmented Perception in Infrared provides a comprehensive review of recent deployment of infrared sensors in modern applications of computer vision, along with in-depth description of the world's best machine vision algorithms and intel- gent analytics. Its topics encompass many disciplines of machine vision, including remote sensing, automatic target detection and recognition, background modeling and image segmentation, object tracking, face and facial expression recognition, - variant shape characterization, disparate sensors fusion, noncontact physiological measurements, night vision, and target classi?cation. Its application scope includes homeland security, public transportation, surveillance, medical, and military. Mo- over, this book emphasizes the merging of the aforementioned machine perception applications and nonvisual imaging in intensi?ed, near infrared, thermal infrared, laser, polarimetric, and hyperspectral bands.

Every mathematical discipline goes through three periods of development: the naive, the formal, and the critical. David Hilbert The goal of this book is to explain the principles that made support vector machines (SVMs) a successful modeling and prediction tool for a variety of applications. We try to achieve this by presenting the basic ideas of SVMs together with the latest developments and current research questions in a uni?ed style. In a nutshell, we identify at least three reasons for the success of SVMs: their ability to learn well with only a very small number of free parameters, their robustness against several types of model violations and outliers, and last but not least their computational e?ciency compared with several other methods. Although there are several roots and precursors of SVMs, these methods gained particular momentum during the last 15 years since Vapnik (1995, 1998) published his well-known textbooks on statistical learning theory with aspecialemphasisonsupportvectormachines. Sincethen,the?eldofmachine learninghaswitnessedintenseactivityinthestudyofSVMs,whichhasspread moreandmoretootherdisciplinessuchasstatisticsandmathematics. Thusit seems fair to say that several communities are currently working on support vector machines and on related kernel-based methods. Although there are many interactions between these communities, we think that there is still roomforadditionalfruitfulinteractionandwouldbegladifthistextbookwere found helpful in stimulating further research. Many of the results presented in this book have previously been scattered in the journal literature or are still under review. As a consequence, these results have been accessible only to a relativelysmallnumberofspecialists,sometimesprobablyonlytopeoplefrom one community but not the others.

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 LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume XVIII includes extensions of papers from the Joint Rough Set Symposium (JRS 2012), which was held in Chengdu, China, in August 2012. The seven papers that constitute this volume deal with topics such as: rough fuzzy sets, intuitionistic fuzzy sets, multi-granulation rough sets, decision-theoretic rough sets, three-way decisions and their applications in attribute reduction, feature selection, overlapping clustering, data mining, cost-sensitive learning, face recognition, and spam filtering.

This book constitutes the refereed proceedings of the 7th International Conference on Similarity Search and Applications, SISAP 2014, held in A Coruna, Spain, in October 2014. The 21 full papers and 6 short papers presented were carefully reviewed and selected from 45 submissions. The papers are organized in topical sections on Improving Similarity Search Methods and Techniques; Indexing and Applications; Metrics and Evaluation; New Scenarios and Approaches; Applications and Specific Domains.

This book constitutes the refereed proceedings of the 15th IFIP TC 6/TC 11 International Conference on Communications and Multimedia Security, CMS 2014, held in Aveiro, Portugal, in September 2014. The 4 revised full papers presented together with 6 short papers, 3 extended abstracts describing the posters that were discussed at the conference, and 2 keynote talks were carefully reviewed and selected from 22 submissions. The papers are organized in topical sections on vulnerabilities and threats, identification and authentification, applied security.

The three-volume set LNCS 8673, 8674, and 8675 constitutes the refereed proceedings of the 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014, held in Boston, MA, USA, in September 2014. Based on rigorous peer reviews, the program committee carefully selected 253 revised papers from 862 submissions for presentation in three volumes. The 100 papers included in the second volume have been organized in the following topical sections: biophysical modeling and simulation; atlas-based transfer of boundary conditions for biomechanical simulation; temporal and motion modeling; computer-aided diagnosis; pediatric imaging; endoscopy; ultrasound imaging; machine learning; cardiovascular imaging; intervention planning and guidance; and brain.

Consumer electronics (CE) devices, providing multimedia entertainment and enabling communication, have become ubiquitous in daily life. However, consumer interaction with such equipment currently requires the use of devices such as remote controls and keyboards, which are often inconvenient, ambiguous and non-interactive. An important challenge for the modern CE industry is the design of user interfaces for CE products that enable interactions which are natural, intuitive and fun. As many CE products are supplied with microphones and cameras, the exploitation of both audio and visual information for interactive multimedia is a growing field of research. Collecting together contributions from an international selection of experts, including leading researchers in industry, this unique text presents the latest advances in applications of multimedia interaction and user interfaces for consumer electronics. Covering issues of both multimedia content analysis and human-machine interaction, the book examines a wide range of techniques from computer vision, machine learning, audio and speech processing, communications, artificial intelligence and media technology. Topics and features: introduces novel computationally efficient algorithms to extract semantically meaningful audio-visual events; investigates modality allocation in intelligent multimodal presentation systems, taking into account the cognitive impacts of modality on human information processing; provides an overview on gesture control technologies for CE; presents systems for natural human-computer interaction, virtual content insertion, and human action retrieval; examines techniques for 3D face pose estimation, physical activity recognition, and video summary quality evaluation; discusses the features that characterize the new generation of CE and examines how web services can be integrated with CE products for improved user experience. This book is an essential resource for researchers and practitioners from both academia and industry working in areas of multimedia analysis, human-computer interaction and interactive user interfaces. Graduate students studying computer vision, pattern recognition and multimedia will also find this a useful reference.

This book considers biometric technology in a broad light, integrating the concept seamlessly into mainstream IT, while discussing the cultural attitudes and the societal impact of identity management. Features: summarizes the material covered at the beginning of every chapter, and provides chapter-ending review questions and discussion points; reviews identity verification in nature, and early historical interest in anatomical measurement; provides an overview of biometric technology, presents a focus on biometric systems and true systems integration, examines the concept of identity management, and predicts future trends; investigates performance issues in biometric systems, the management and security of biometric data, and the impact of mobile devices on biometrics technology; explains the equivalence of performance across operational nodes, introducing the APEX system; considers the legal, political and societal factors of biometric technology, in addition to user psychology and other human factors.

Micromechanical manufacturing based on microequipment creates new possibi- ties in goods production. If microequipment sizes are comparable to the sizes of the microdevices to be produced, it is possible to decrease the cost of production drastically. The main components of the production cost - material, energy, space consumption, equipment, and maintenance - decrease with the scaling down of equipment sizes. To obtain really inexpensive production, labor costs must be reduced to almost zero. For this purpose, fully automated microfactories will be developed. To create fully automated microfactories, we propose using arti?cial neural networks having different structures. The simplest perceptron-like neural network can be used at the lowest levels of microfactory control systems. Adaptive Critic Design, based on neural network models of the microfactory objects, can be used for manufacturing process optimization, while associative-projective neural n- works and networks like ART could be used for the highest levels of control systems. We have examined the performance of different neural networks in traditional image recognition tasks and in problems that appear in micromechanical manufacturing. We and our colleagues also have developed an approach to mic- equipment creation in the form of sequential generations. Each subsequent gene- tion must be of a smaller size than the previous ones and must be made by previous generations. Prototypes of ?rst-generation microequipment have been developed and assessed.

This book constitutes the refereed proceedings of the 9th Chinese Conference on Biometric Recognition, CCBR 2014, held in Shenyang, China, in November 2014. The 60 revised full papers presented were carefully reviewed and selected from among 90 submissions. The papers focus on face, fingerprint and palmprint, vein biometrics, iris and ocular biometrics, behavioral biometrics, application and system of biometrics, multi-biometrics and information fusion, other biometric recognition and processing.

Automatic personal authentication using biometric information is becoming more essential in applications of public security, access control, forensics, banking, etc. Many kinds of biometric authentication techniques have been developed based on different biometric characteristics. However, most of the physical biometric recognition techniques are based on two dimensional (2D) images, despite the fact that human characteristics are three dimensional (3D) surfaces. Recently, 3D techniques have been applied to biometric applications such as 3D face, 3D palmprint, 3D fingerprint, and 3D ear recognition. This book introduces four typical 3D imaging methods, and presents some case studies in the field of 3D biometrics. This book also includes many efficient 3D feature extraction, matching, and fusion algorithms. These 3D imaging methods and their applications are given as follows: - Single view imaging with line structured-light: 3D ear identification - Single view imaging with multi-line structured-light: 3D palmprint authentication - Single view imaging using only 3D camera: 3D hand verification - Multi-view imaging: 3D fingerprint recognition 3D Biometrics: Systems and Applications is a comprehensive introduction to both theoretical issues and practical implementation in 3D biometric authentication. It will serve as a textbook or as a useful reference for graduate students and researchers in the fields of computer science, electrical engineering, systems science, and information technology. Researchers and practitioners in industry and R&D laboratories working on security system design, biometrics, immigration, law enforcement, control, and pattern recognition will also find much of interest in this book.

This small book addresses different kinds of datafiles, as commonly encountered in clinical research, and their data-analysis on SPSS Software. Some 15 years ago serious statistical analyses were conducted by specialist statisticians using ma- frame computers. Nowadays, there is ready access to statistical computing using personal computers or laptops, and this practice has changed boundaries between basic statistical methods that can be conveniently carried out on a pocket calculator and more advanced statistical methods that can only be executed on a computer. Clinical researchers currently perform basic statistics without professional help from a statistician, including t-tests and chi-square tests. With help of user-friendly software the step from such basic tests to more complex tests has become smaller, and more easy to take. It is our experience as masters' and doctorate class teachers of the European College of Pharmaceutical Medicine (EC Socrates Project Lyon France) that s- dents are eager to master adequate command of statistical software for that purpose. However, doing so, albeit easy, still takes 20-50 steps from logging in to the final result, and all of these steps have to be learned in order for the procedures to be successful.