This book constitutes the refereed proceedings of the First International Conference on Biomedical Informatics and Technology, ACBIT 2013, held in Aizu-Wakamatsu, Japan, in September 2013. The ??? revised full papers presented together with 14 keynotes and invited talks were carefully reviewed and selected from 48 submissions. The papers address important problems in medicine, biology and health using image analysis, computer vision, pattern analysis and classification, information visualization, signal processing, control theory, information theory, statistical analysis, information fusion, numerical analysis, fractals and chaos, optimization, simulation and modeling, parallel computing, computational intelligence methods, machine learning, data mining, decision support systems, database integration and management, cognitive modeling, and applied linguistics.

"Reliable Knowledge Discovery" focuses on theory, methods, and techniques for RKDD, a new sub-field of KDD. It studies the theory and methods to assure the reliability and trustworthiness of discovered knowledge and to maintain the stability and consistency of knowledge discovery processes. RKDD has a broad spectrum of applications, especially in critical domains like medicine, finance, and military.

"Reliable Knowledge Discovery" also presents methods and techniques for designing robust knowledge-discovery processes. Approaches to assessing the reliability of the discovered knowledge are introduced. Particular attention is paid to methods for reliable feature selection, reliable graph discovery, reliable classification, and stream mining. Estimating the data trustworthiness is covered in this volume as well. Case studies are provided in many chapters.

"Reliable Knowledge Discovery" is designed for researchers and advanced-level students focused on computer science and electrical engineering as a secondary text or reference. Professionals working in this related field and KDD application developers will also find this book useful.

This book constitutes the refereed proceedings of the 10th Chinese Conference on Advances in Image and Graphics Technologies, IGTA 2015, held in Beijing, China, in June 2015. The 50 papers presented were carefully reviewed and selected from 138 submissions. They provide a forum for sharing new aspects of the progresses in the areas of image processing technology, image analysis und understanding, computer vision and pattern recognition, big data mining, computer graphics and VR, image technology application.

This groundbreaking resource offers a comprehensive overview of cutting-edge video-based eye monitoring algorithms, as well as human factor algorithms and experiments. Helping to apply the skills in Intelligent Human Machine Interaction (IHMI), this practical reference shows how the core low-level building blocks are implemented and how they are linked with human factor algorithms and human-machine interfaces (HMI) in smart vehicles, sensitive environments and medical facilities.

3D Surface Reconstruction: Multi-Scale Hierarchical Approaches presents methods to model 3D objects in an incremental way so as to capture more finer details at each step. The configuration of the model parameters, the rationale and solutions are described and discussed in detail so the reader has a strong understanding of the methodology. Modeling starts from data captured by 3D digitizers and makes the process even more clear and engaging. Innovative approaches, based on two popular machine learning paradigms, namely Radial Basis Functions and the Support Vector Machines, are also introduced. These paradigms are innovatively extended to a multi-scale incremental structure, based on a hierarchical scheme. The resulting approaches allow readers to achieve high accuracy with limited computational complexity, and makes the approaches appropriate for online, real-time operation. Applications can be found in any domain in which regression is required. 3D Surface Reconstruction: Multi-Scale Hierarchical Approaches is designed as a secondary text book or reference for advanced-level students and researchers in computer science. This book also targets practitioners working in computer vision or machine learning related fields.

Biological systems are a source of inspiration in the development of small autonomous sensor nodes. The two major types of optical vision systems found in nature are the single aperture human eye and the compound eye of insects. The latter are among the most compact and smallest vision sensors. The eye is a compound of individual lenses with their own photoreceptor arrays. The visual system of insects allows them to fly with a limited intelligence and brain processing power. A CMOS image sensor replicating the perception of vision in insects is discussed and designed in this book for industrial (machine vision) and medical applications. The CMOS metal layer is used to create an embedded micro-polarizer able to sense polarization information. This polarization information is shown to be useful in applications like real time material classification and autonomous agent navigation. Further the sensor is equipped with in pixel analog and digital memories which allow variation of the dynamic range and in-pixel binarization in real time. The binary output of the pixel tries to replicate the flickering effect of the insect's eye to detect smallest possible motion based on the change in state. An inbuilt counter counts the changes in states for each row to estimate the direction of the motion. The chip consists of an array of 128x128 pixels, it occupies an area of 5 x 4 mm2 and it has been designed and fabricated in an 180nm CMOS CIS process from UMC.

This book constitutes the thoroughly refereed post-workshop proceedings of the Third IAPR TC3 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2014, held in Stockholm, Sweden, in August 2014, as a satellite event of the International Conference on Pattern Recognition, ICPR 2014. The 14 revised papers presented focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition, user identification, and recognition of human activities.

This book presents theoretical and practical aspects of the interaction between low and high level image processing. Multiresolution analysis owes its popularity mostly to wavelets and is widely used in a variety of applications. Low level image processing is important for the performance of many high level applications. The book includes examples from different research fields, i.e. video surveillance; biomedical applications (EMG and X-ray); improved communication, namely teleoperation, telemedicine, animation, augmented/virtual reality and robot vision; monitoring of the condition of ship systems and image quality control.

This book provides a state-of-the art overview of satellite archaeology and it is an invaluable volume for archaeologists, scientists, and managers interested in using satellite Earth Observation (EO) to improve the traditional approach for archaeological investigation, protection and management of Cultural Heritage.

The recent increasing development of EO techniques and the tremendous advances in Information and Communication Technologies (ICT) have resulted primarily in Cultural Heritage applications. The book focuses on new challenging prospects for the use of EO in archaeology not only for probing the subsurface to unveil sites and artifacts, but also for the management and valorization as well as for the monitoring and preservation of cultural resources. The book provides a first-class understanding of this revolutionary scenario which was unthinkable several years ago.

The book offers: (i) an excellent collection of outstanding articles focusing on satellite data processing, analysis and interpretation for archaeological applications, (ii) impressive case studies, (iii) striking examples of the high potential of the integration of multi-temporal, multi-scale, multi-sensors techniques.

Each chapter is composed as an authoritative contribution to help the reader grasp the value of its content. The authors are renowned experts from the international scientific community.

"Audience" This book will be of interest to scientists in remote sensing applied to archeology, geoarcheology, paleo-environment, paleo-climate and cultural heritage.

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Mathematical Methods for Signal and Image Analysis and Representation presents the mathematical methodology for generic image analysis tasks. In the context of this book an image may be any m-dimensional empirical signal living on an n-dimensional smooth manifold (typically, but not necessarily, a subset of spacetime). The existing literature on image methodology is rather scattered and often limited to either a deterministic or a statistical point of view. In contrast, this book brings together these seemingly different points of view in order to stress their conceptual relations and formal analogies. Furthermore, it does not focus on specific applications, although some are detailed for the sake of illustration, but on the methodological frameworks on which such applications are built, making it an ideal companion for those seeking a rigorous methodological basis for specific algorithms as well as for those interested in the fundamental methodology per se. Covering many topics at the forefront of current research, including anisotropic diffusion filtering of tensor fields, this book will be of particular interest to graduate and postgraduate students and researchers in the fields of computer vision, medical imaging and visual perception.

This book presents a thorough and detailed guide to image registration, outlining the principles and reviewing state-of-the-art tools and methods. The book begins by identifying the components of a general image registration system, and then describes the design of each component using various image analysis tools. The text reviews a vast array of tools and methods, not only describing the principles behind each tool and method, but also measuring and comparing their performances using synthetic and real data. Features: discusses similarity/dissimilarity measures, point detectors, feature extraction/selection and homogeneous/heterogeneous descriptors; examines robust estimators, point pattern matching algorithms, transformation functions, and image resampling and blending; covers principal axes methods, hierarchical methods, optimization-based methods, edge-based methods, model-based methods, and adaptive methods; includes a glossary, an extensive list of references, and an appendix on PCA.

Image registration is required whenever images need to be compared, merged or integrated after they have been taken at different times, from different viewpoints, and/or by different sensors. Registration, also known as alignment, fusion, or warping, is the process of transforming data into a common reference frame. This book provides an overview of state-of-the-art registration techniques from theory to practice, plus numerous exercises designed to enhance readers' understanding of the principles and mechanisms of the described techniques. It also provides, via a supplementary Web page, free access to FAIR.m, a package that is based on the MATLAB(r) software environment, which enables readers to experiment with the proposed algorithms and explore the presented examples in much more depth. Written from an interdisciplinary point of view, this book will appeal to mathematicians, medical imaging professionals and computer scientists and engineers.

This work proposes strategies and solutions to tackle the problem of building photo-mosaics of very large underwater optical surveys, presenting contributions to the image preprocessing, enhancing and blending steps, and resulting in an improved visual quality of the final photo-mosaic. The text opens with a comprehensive review of mosaicing and blending techniques, before proposing an approach for large scale underwater image mosaicing and blending. In the image preprocessing step, a depth dependent illumination compensation function is used to solve the non-uniform illumination appearance due to light attenuation. For image enhancement, the image contrast variability due to different acquisition altitudes is compensated using an adaptive contrast enhancement based on an image quality reference selected through a total variation criterion. In the blending step, a graph-cut strategy operating in the image gradient domain over the overlapping regions is suggested. Next, an out-of-core blending strategy for very large scale photo-mosaics is presented and tested on real data. Finally, the performance of the approach is evaluated and compared with other approaches.

Nowadays, intelligent techniques are more and more used in Computer Graphics in order to optimise the processing time, to find more accurate solutions for a lot of Computer Graphics problems, than with traditional methods, or simply to find solutions in problems where traditional methods fail. The purpose of this volume is to present current work of the Intelligent Computer Graphics community, a community growing up year after year. This volume is a kind of continuation of the previously published Springer volumes "Artificial Intelligence Techniques for Computer Graphics" (2008) and "Intelligent Computer Graphics 2009" (2009). This volume contains selected extended papers from the last 3IA Conference (3IA'2010), which has been held in Athens (Greece) in May 2010. This year papers are particularly exciting and concern areas like rendering, viewpoint quality, data visualisation, vision, computational aesthetics, scene understanding, intelligent lighting, declarative modelling, GIS, scene reconstruction and other important themes.

This volume constitutes the refereed proceedings of the 10th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2015, held in Hong Kong, China, in January 2015. The 36 revised full papers were carefully reviewed and selected from 45 submissions. The papers are organized in topical sections on discrete and continuous optimization; image restoration and inpainting; segmentation; PDE and variational methods; motion, tracking and multiview reconstruction; statistical methods and learning; and medical image analysis.

This book constitutes the proceedings of the 22nd International Symposium on Graph Drawing, GD 2014, held in Wurzburg, Germany, in September 2014. The 41 full papers presented in this volume were carefully reviewed and selected from 72 submissions. The back matter of the book also contains 2 page poster papers presented at the conference. The contributions are organized in topical sections named: planar subgraphs; simultaneous embeddings; applications; contact representations; k-planar graphs; crossing minimization; level drawings; theory; fixed edge directions; drawing under constraints; clustered planarity; and greedy graphs.

Beginning Android 3D Game Development is a unique, examples-driven book for today's Android and game app developers who want to learn how to build 3D game apps that run on the latest Android 5.0 (KitKat) platform using Java and OpenGL ES. Android game app development continues to be one of the hottest areas where indies and existing game app developers seem to be most active. Android is the second best mobile apps eco and arguably even a hotter game apps eco than iOS. 3D makes your games come alive; so in this book you'll find that we go in depth on creating 3D games for the Android platform with OpenGL ES 2.0 using an original case study game called Drone Grid. Moreover, this book offers an extensive case study with code that will be modular and re-useable helping you create your own games using advanced vertex and fragment shaders. Drone Grid is a game app case study that is somewhat similar to the best selling Geometry Wars game series utilizing a gravity grid and colorful abstract graphics and particles. After reading and using this book, you'll be able to build your first 3D Android game app for smartphones and tablets. You may even be able to upload and sell from popular Android app stores like Google Play and Amazon Appstore.

Edited by some of the most experienced authors in the field, Biomedical Imaging provides comprehensive coverage on medical and biological imaging. Original research and critical reviews on software and hardware technologies for medical and biological imaging tasks are presented in the book, along with data processing in all imaging modalities for molecular, cellular, anatomical and functional imaging. Research topics include image acquisition, registration, reconstruction, multimodality methods, noise filtering and image enhancement, segmentation, classification and feature detection, model and atlas based imaging, as well as system development and acceleration technologies. Biomedical Imaging is comprised of 40 contributed chapters, which are organized in such a way that researchers, engineers, clinical practitioners and graduate students can easily follow up with relevant topics, and will benefit from reading the views of the domain experts in their fields.

This book presents a comprehensive treatment of visual analysis of behaviour from computational-modelling and algorithm-design perspectives. Topics: covers learning-group activity models, unsupervised behaviour profiling, hierarchical behaviour discovery, learning behavioural context, modelling rare behaviours, and "man-in-the-loop" active learning; examines multi-camera behaviour correlation, person re-identification, and "connecting-the-dots" for abnormal behaviour detection; discusses Bayesian information criterion, Bayesian networks, "bag-of-words" representation, canonical correlation analysis, dynamic Bayesian networks, Gaussian mixtures, and Gibbs sampling; investigates hidden conditional random fields, hidden Markov models, human silhouette shapes, latent Dirichlet allocation, local binary patterns, locality preserving projection, and Markov processes; explores probabilistic graphical models, probabilistic topic models, space-time interest points, spectral clustering, and support vector machines.

In den letzten Jahren hat sich der Workshop "Bildverarbeitung fur die Medizin" durch erfolgreiche Veranstaltungen etabliert. Ziel ist auch 2014 wieder die Darstellung aktueller Forschungsergebnisse und die Vertiefung der Gesprache zwischen Wissenschaftlern, Industrie und Anwendern. Die Beitrage dieses Bandes - einige davon in englischer Sprache - umfassen alle Bereiche der medizinischen Bildverarbeitung, insbesondere Bildgebung und -akquisition, Molekulare Bildgebung, Visualisierung und Animation, Bildsegmentierung und -fusion, Anatomische Atlanten, Zeitreihenanalysen, Biomechanische Modellierung, Klinische Anwendung computerunterstutzter Systeme, Validierung und Qualitatssicherung u.v.m.

This book constitutes the refereed proceedings of the 13th International Conference on Entertainment Computing, ICEC 2014, held in Sydney, Australia, in October 2013. The 20 full papers, 6 short papers and 8 posters presented were carefully reviewed and selected from 62 submissions. In addition to these papers, the program featured 3 demonstration papers, and 2 workshops. The papers cover various aspects of entertainment computing including authoring, development, use and evaluation of digital entertainment artefacts and processes.

Face detection and recognition are the nonintrusive biometrics of choice in many security applications. Examples of their use include border control, driver's license issuance, law enforcement investigations, and physical access control. Face Detection and Recognition: Theory and Practice elaborates on andexplains the theory and practice of face detection and recognition systems currently in vogue. The book begins with an introduction to the state of the art, offering a general review of the available methods and an indication of future research using cognitive neurophysiology. The text then: Explores subspace methods for dimensionality reduction in face image processing, statistical methods applied to face detection, and intelligent face detection methods dominated by the use of artificial neural networks Covers face detection with colour and infrared face images, face detection in real time, face detection and recognition using set estimation theory, face recognition using evolutionary algorithms, and face recognition in frequency domain Discusses methods for the localization of face landmarks helpful in face recognition, methods of generating synthetic face images using set estimation theory, and databases of face images available for testing and training systems Features pictorial descriptions of every algorithm as well as downloadable source code (in MATLAB (R)/PYTHON) and hardware implementation strategies with code examples Demonstrates how frequency domain correlation techniques can be used supplying exhaustive test results Face Detection and Recognition: Theory and Practice provides students, researchers, and practitioners with a single source for cutting-edge information on the major approaches, algorithms, and technologies used in automated face detection and recognition.

This book constitutes the thoroughly refereed post-conference proceedings of the International Conference on Nature of Computation and Communication, ICTCC 2014, held in November 2014 in Ho Chi Minh City, Vietnam. The 34 revised full papers presented were carefully reviewed and selected from over 100 submissions. The papers cover formal methods for self-adaptive systems and discuss natural approaches and techniques for computation and communication.

This book constitutes the thoroughly refereed conference proceedings of the 9th International Workshop on Algorithms and Computation, WALCOM 2015, held in Dhaka, Bangladesh, in February 2015. The 26 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 85 submissions. The papers are organized in topical sections on approximation algorithms, data structures and algorithms, computational geometry, combinatorial algorithms, distributed and online algorithms, graph drawing and algorithms, combinatorial problems and complexity, and graph enumeration and algorithms.