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Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision
Networked computers are ubiquitous, and are subject to attack, misuse, and abuse. One method to counteracting this cyber threat is to provide security analysts with better tools to discover patterns, detect anomalies, identify correlations, and communicate their findings. Visualization for computer security (VizSec) researchers and developers are doing just that. VizSec is about putting robust information visualization tools into the hands of human analysts to take advantage of the power of the human perceptual and cognitive processes in solving computer security problems. This volume collects the papers presented at the 4th International Workshop on Computer Security - VizSec 2007.
Since the dawn of the new millennium, robotics has undergone a major transf- mation in scope and dimensions. This expansion has been brought about by the maturityofthe?eldandtheadvancesinitsrelatedtechnologies.Fromapred- inantly industrial focus, robotics has been rapidly expanding into the challenges of the human world. The new generation of robots is expected to safely and dependably cohabit with humans in homes, workplaces, and communities, p- viding support in services, entertainment, education, healthcare, manufacturing, and assistance. Beyond its impact on physical robots, the body of knowledge robotics has produced is revealing a much wider rangeof applications reaching across diverse research areas and scienti?c disciplines, such as: biomechanics, haptics, neu- sciences, virtual prototyping, animation, surgery, and sensor networks among others. In return, the challenges of the new emerging areas are proving an ab- dant source of stimulation and insights for the ?eld of robotics. It is indeed at the intersection of disciplines that the most striking advances happen. The goal of the series of Springer Tracts in Advanced Robotics (STAR)isto bring, in a timely fashion, the latest advances and developments in robotics on thebasisoftheirsigni?canceandquality.Itisourhopethatthewiderdissemi- tion of research developments will stimulate more exchanges and collaborations among the research community and contribute to further advancement of this rapidly growing ?e
Recent progress in research, teaching and communication has arisen
from the use of new tools in visualization. To be fruitful,
visualization needs precision and beauty. This book is a source of
mathematical illustrations by mathematicians as well as artists. It
offers examples in many basic mathematical fields including
polyhedra theory, group theory, solving polynomial equations,
dynamical systems and differential topology.
One of the grand challenges for computational intelligence and biometrics is to understand how people process and recognize faces and to develop automated and reliable face recognition systems. Biometrics has become the major component in the complex decision making process associated with security applications. The many challenges addressed for face detection and authentication include cluttered environments, occlusion and disguise, temporal changes, and last but not least, robust training and open set testing. Reliable Face Recognition Methods seeks to comprehensively address the face recognition problem while drawing inspiration and gaining new insights from complementary fields of endeavor such as neurosciences, statistics, signal and image processing, computer vision, and machine learning and data mining. The book examines the evolution of research surrounding the field to date, explores new directions, and offers specific guidance on the most promising venues for future R&D. With its well-focused approach and clarity of presentation, this new text/reference is an excellent resource for computer scientists and engineers, researchers, and professionals who need to learn about face recognition. In addition, the book is ideally suited to students studying biometrics, pattern recognition, and human-computer interaction.
This book approaches the realisation of digital terrain and landscape data through clear and practical examples. From data provision and the creation of revealing analyses to realistic depictions for presentation purposes, the reader is led through the world of digital 3-D graphics. The authors deep knowledge of the scientific fundamentals and many years of experience in 3-D visualization enable them to lead the reader through a complex subject and shed light on previously murky virtual landscapes.
Many computer scientists, engineers, applied mathematicians, and physicists use geometry theory and geometric computing methods in the design of perception-action systems, intelligent autonomous systems, and man-machine interfaces. This handbook brings together the most recent advances in the application of geometric computing for building such systems, with contributions from leading experts in the important fields of neuroscience, neural networks, image processing, pattern recognition, computer vision, uncertainty in geometric computations, conformal computational geometry, computer graphics and visualization, medical imagery, geometry and robotics, and reaching and motion planning. For the first time, the various methods are presented in a comprehensive, unified manner. This handbook is highly recommended for postgraduate students and researchers working on applications such as automated learning; geometric and fuzzy reasoning; human-like artificial vision; tele-operation; space maneuvering; haptics; rescue robots; man-machine interfaces; tele-immersion; computer- and robotics-aided neurosurgery or orthopedics; the assembly and design of humanoids; and systems for metalevel reasoning.
The authors here provide a detailed treatment of the design of robust adaptive controllers for nonlinear systems with uncertainties. They employ a new tool based on the ideas of system immersion and manifold invariance. New algorithms are delivered for the construction of robust asymptotically-stabilizing and adaptive control laws for nonlinear systems. The methods proposed lead to modular schemes that are easier to tune than their counterparts obtained from Lyapunov redesign.
Ambient Intelligence (AmI) is an integrating technology for supporting a pervasive and transparent infrastructure for implementing smart environments. Such technology is used to enable environments for detecting events and behaviors of people and for responding in a contextually relevant fashion. AmI proposes a multi-disciplinary approach for enhancing human machine interaction. Ambient Intelligence: A Novel Paradigm is a compilation of edited chapters describing current state-of-the-art and new research techniques including those related to intelligent visual monitoring, face and speech recognition, innovative education methods, as well as smart and cognitive environments. The authors start with a description of the iDorm as an example of a smart environment conforming to the AmI paradigm, and introduces computer vision as an important component of the system. Other computer vision examples describe visual monitoring for the elderly, classic and novel surveillance techniques using clusters of cameras installed in indoor and outdoor application domains, and the monitoring of public spaces. Face and speech recognition systems are also covered as well as enhanced LEGO blocks for novel educational purposes. The book closes with a provocative chapter on how a cybernetic system can be designed as the backbone of a human machine interaction.
Face detection, because of its vast array of applications, is one of the most active research areas in computer vision. In this book, we review various approaches to face detection developed in the past decade, with more emphasis on boosting-based learning algorithms. We then present a series of algorithms that are empowered by the statistical view of boosting and the concept of multiple instance learning. We start by describing a boosting learning framework that is capable to handle billions of training examples. It differs from traditional bootstrapping schemes in that no intermediate thresholds need to be set during training, yet the total number of negative examples used for feature selection remains constant and focused (on the poor performing ones). A multiple instance pruning scheme is then adopted to set the intermediate thresholds after boosting learning. This algorithm generates detectors that are both fast and accurate. We then present two multiple instance learning schemes for face detection, multiple instance learning boosting (MILBoost) and winner-take-all multiple category boosting (WTA-McBoost). MILBoost addresses the uncertainty in accurately pinpointing the location of the object being detected, while WTA-McBoost addresses the uncertainty in determining the most appropriate subcategory label for multiview object detection. Both schemes can resolve the ambiguity of the labeling process and reduce outliers during training, which leads to improved detector performances. In many applications, a detector trained with generic data sets may not perform optimally in a new environment. We propose detection adaption, which is a promising solution for this problem. We present an adaptation scheme based on the Taylor expansion of the boosting learning objective function, and we propose to store the second order statistics of the generic training data for future adaptation. We show that with a small amount of labeled data in the new environment, the detector's performance can be greatly improved. We also present two interesting applications where boosting learning was applied successfully. The first application is face verification for filtering and ranking image/video search results on celebrities. We present boosted multi-task learning (MTL), yet another boosting learning algorithm that extends MILBoost with a graphical model. Since the available number of training images for each celebrity may be limited, learning individual classifiers for each person may cause overfitting. MTL jointly learns classifiers for multiple people by sharing a few boosting classifiers in order to avoid overfitting. The second application addresses the need of speaker detection in conference rooms. The goal is to find who is speaking, given a microphone array and a panoramic video of the room. We show that by combining audio and visual features in a boosting framework, we can determine the speaker's position very accurately. Finally, we offer our thoughts on future directions for face detection. Table of Contents: A Brief Survey of the Face Detection Literature / Cascade-based Real-Time Face Detection / Multiple Instance Learning for Face Detection / Detector Adaptation / Other Applications / Conclusions and Future Work
Welcome to the Proceedings of ICCHP 2010! We were proud to welcome participants from more than 40 countries from all over the world to this year's ICCHP. Since the late 1980s, it has been ICCHP's mission to support and reflect development in the field of "Assistive Technologies," eAccessibility and eInclusion. With a focus on scientific quality, ICCHP has become an important reference in our field. The 2010 conference and this collection of papers once again fulfilled this mission. The International Programme Committee, comprising 106 experts from all over the world, selected 147 full and 44 short papers out of 328 abstracts submitted to ICCHP. This acceptance ratio of about half of the submissions demonstrates our strict pursuit of scientific quality both of the programme and in particular of the proceedings in your hands. An impressive number of experts agreed to organize "Special Thematic Sessions" (STS) for ICCHP 2010. These STS help to bring the meeting into sharper focus in several key areas. In turn, this deeper level of focus helps to collate a state of the art and mainstream technical, social, cultural and political developments.
Appendix 164 3. A 3. A. 1 Approximate Estimation of Fundamental Matrix from General Matrix 164 3. A. 2 Estimation of Affine Transformation 165 4 RECOVERY OF EPIPOLAR GEOMETRY FROM LINE SEGMENTS OR LINES 167 Line Segments or Straight Lines 168 4. 1 4. 2 Solving Motion Using Line Segments Between Two Views 173 4. 2. 1 Overlap of Two Corresponding Line Segments 173 Estimating Motion by Maximizing Overlap 175 4. 2. 2 Implementation Details 4. 2. 3 176 Reconstructing 3D Line Segments 4. 2. 4 179 4. 2. 5 Experimental Results 180 4. 2. 6 Discussions 192 4. 3 Determining Epipolar Geometry of Three Views 194 4. 3. 1 Trifocal Constraints for Point Matches 194 4. 3. 2 Trifocal Constraints for Line Correspondences 199 4. 3. 3 Linear Estimation of K, L, and M Using Points and Lines 200 4. 3. 4 Determining Camera Projection Matrices 201 4. 3. 5 Image Transfer 203 4. 4 Summary 204 5 REDEFINING STEREO, MOTION AND OBJECT RECOGNITION VIA EPIPOLAR GEOMETRY 205 5. 1 Conventional Approaches to Stereo, Motion and Object Recognition 205 5. 1. 1 Stereo 205 5. 1. 2 Motion 206 5. 1. 3 Object Recognition 207 5. 2 Correspondence in Stereo, Motion and Object Recognition as 1D Search 209 5. 2. 1 Stereo Matching 209 xi Contents 5. 2. 2 Motion Correspondence and Segmentation 209 5. 2. 3 3D Object Recognition and Localization 210 Disparity and Spatial Disparity Space 210 5.
One of the most natural representations for modelling spatial objects in computers is discrete representations in the form of a 2D square raster and a 3D cubic grid, since these are naturally obtained by segmenting sensor images. However, the main difficulty is that discrete representations are only approximations of the original objects, and can only be as accurate as the cell size allows. If digitisation is done by real sensor devices, then there is the additional difficulty of sensor distortion. To overcome this, digital shape features must be used that abstract from the inaccuracies of digital representation. In order to ensure the correspondence of continuous and digital features, it is necessary to relate shape features of the underlying continuous objects and to determine the necessary resolution of the digital representation. This volume gives an overview and a classification of the actual approaches to describe the relation between continuous and discrete shape features that are based on digital geometric concepts of discrete structures. Audience: This book will be of interest to researchers and graduate students whose work involves computer vision, image processing, knowledge representation or representation of spatial objects.
Invariant, or coordinate-free methods provide a natural framework for many geometric questions. Invariant Methods in Discrete and Computational Geometry provides a basic introduction to several aspects of invariant theory, including the supersymmetric algebra, the Grassmann-Cayler algebra, and Chow forms. It also presents a number of current research papers on invariant theory and its applications to problems in geometry, such as automated theorem proving and computer vision. Audience: Researchers studying mathematics, computers and robotics.
Integrates computer vision, pattern recognition, and AI. Presents original research that will benefit researchers and professionals in computer vision, pattern recognition, target recognition, machine learning, evolutionary learning, image processing, knowledge discovery and data mining, cybernetics, robotics, automation and psychology
It givesus greatpleasureto presentthe proceedings of the 9th Asian Conference on Computer Vision (ACCV 2009), held in Xi'an, China, in September 2009. This was the ?rst ACCV conference to take place in mainland China. We received a total of 670 full submissions, which is a new record in the ACCV series. Overall, 35 papers were selected for oral presentation and 131 as posters, yielding acceptance rates of 5.2% for oral, 19.6% for poster, and 24.8% in total. In the paper reviewing, we continued the tradition of previous ACCVsbyconductingtheprocessinadouble-blindmanner.Eachofthe33Area Chairs received a pool of about 20 papers and nominated a number of potential reviewers for each paper. Then, Program Committee Chairs allocated at least three reviewers to each paper, taking into consideration any con?icts of interest and the balance of loads. Once the reviews were ?nished, the Area Chairs made summaryreportsforthepapersintheirpools, basedonthereviewers'comments and on their own assessments of the papers.
Intimesofdecliningeconomicgrowth, companieshavetocontroltheircostsmore than ever to saveresources needed in the future. Regardless of the economic size of the company, the processes of production and logistics play a decisive role in stabilizing procedures and avoiding waste. Both are important cost drivers in manufacturing companies and therefore they o?er large potential savings. Pervasive networking in the last years has contributed to a hitherto unknown transparency of global markets. This harmonization opened up new possibilities of entering foreign markets for procurement and sales to the companies. The emerging global procurement strategy was understood as a chance to rethink the relocation of existing production facilities to pro't from existing di?erences in price and performance as a resource-saving factor. Many companies tended towards a reduction of their vertical integration by outsourcing sections of their value chain. These contracted services of production result in higher transport volumes, increased complexity of supply processes and new requirements on - gistic networks. This trend of outsourcing has not stopped, but is slowing down noticeably. Additionally, thereisanincreasingproportionofcompaniesrestoring business units that were outsourced before. Reasons for turning back decisions are often to be found in missed goals. It is not unusual that important cost f- tors were disregarded in the original basis of decision-making. In the meantime many companies have realized that it is easier to achieve stability of processes and therewith a control of costs by increasing their own contribution to p- duction. Especially in times of under-utilized capacities like in the current crisis, insourcingcanbeastrategicoptio
As our heritage deteriorates through erosion, human error or natural disasters, it has become more important than ever to preserve our past - even if it is in digital form only. This highly relevant work describes thorough research and methods for preserving cultural heritage objects through the use of 3D digital data. These methods were developed via computer vision and computer graphics technologies. They offer a way of passing our heritage down to future generations.
This book focuses on the challenges to biomedical education posed by the lockdowns and restrictions to on campus teaching brought about by the COVID-19 pandemic and highlights the tools and digital visualization technologies that have been successfully developed and used for remote teaching. Biomedical education for science, medical, dental and allied health professionals relies on teaching visual and tactile knowledge using practice-based approaches. This has been delivered for decades via on-campus lectures, workshops and laboratories, teaching practical skills as well as fundamental knowledge and understanding. However, the arrival of the COVID-19 pandemic meant that education across the globe had to pivot very quickly to be able to deliver these skills and knowledge in a predominantly online environment. This brought with it many challenges, as Higher Education staff, had to adapt to deliver these visual subjects remotely. This book addresses the challenges and solutions faced by Higher Education staff in teaching visual content in distance education. Chapters include literature reviews, original research, and pedagogical reflections for a wide range of biomedical subjects, degrees such as medicine, dentistry and veterinary sciences with examples from undergraduate and postgraduate settings. The goal of the book is to provide a compendium of expertise based on evidence gathered during the COVID-19 pandemic, as well as reflections on the challenges and lessons learned from this dramatic shift in teaching. It also presents new examples of best practices that have emerged from this experience to ensure that they are not lost as we return to on-campus learning in a new era of biomedical teaching. This book will be of interest to anyone looking for a helpful reference point when designing online or blended teaching for visual practice-based subjects.
The International Gesture Workshops (GW) are interdisciplinary events for those researching gesture-based communication across the disciplines. The focus of these events is a shared interest in understanding gestures and sign language in their many facets, and using them for advancing human-machine interaction. Since 1996, International Gesture Workshops have been held roughly every second year, with fully reviewed proceedings published by Springer. The International Gesture Workshop GW 2009 was hosted by Bielefeld University's Center for Interdisciplinary Research (ZiF - Zentrum fur interdisziplinare Forschung) during February 25-27, 2009. Like its predecessors, GW 2009 aimed to provide a platform for participants to share, discuss, and criticize recent and novel research with a multidisciplinary audience. More than 70 computer scientists, linguistics, psychologists, neuroscientists as well as dance and music scientists from 16 countries met to present and exchange their newest results under the umbrella theme "Gesture in Embodied Communication and Human-Computer Interaction. " Consistent with the steady growth of research activity in this area, a large number of high-quality submissions were received, which made GW 2009 an exciting and important event for anyone interested in gesture-related technological research relevant to human-computer interaction. In line with the practice of previous gesture workshops, presenters were invited to submit theirs papers for publication in a subsequent peer-reviewed publication of high quality. The present book is the outcome of this effort. Representing the research work from eight countries, it contains a selection of 28 thoroughly reviewed articles.
We are pleased to present this set of peer-reviewed papers from the ?rst MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support. The MICCAI conference has been the ?agship conference for the m- ical imaging community re?ecting the state of the art in techniques of segm- tation, registration, and robotic surgery. Yet, the transfer of these techniques to clinical practice is rarely discussed in the MICCAI conference. To address this gap, we proposed to hold this workshop with MICCAI in London in September 2009. The goal of the workshop was to show the application of content-based retrieval in clinical decision support. With advances in electronic patient record systems, a large number of pre-diagnosed patient data sets are now bec- ing available. These data sets are often multimodal consisting of images (x-ray, CT, MRI), videos and other time series, and textual data (free text reports and structuredclinicaldata). Analyzing thesemultimodalsourcesfordisease-speci?c information across patients can reveal important similarities between patients and hence their underlying diseases and potential treatments. Researchers are now beginning to use techniques of content-based retrieval to search for disea- speci?c information in modalities to ?nd supporting evidence for a disease or to automatically learn associations of symptoms and diseases. Benchmarking frameworks such as ImageCLEF (Image retrieval track in the Cross-Language Evaluation Forum) have expanded over the past ?ve years to include large m- ical image collections for testing various algorithms for medical image retrieval and classi?cation.
One of the greatest scientific challenges of the 21st century is how to master, organize and extract useful knowledge from the overwhelming flow of information made available by today 's data acquisition systems and computing resources. Visualization is the premium means of taking up this challenge. This book is based on selected lectures given by leading experts in scientific visualization during a workshop held at Schloss Dagstuhl, Germany. Topics include user issues in visualization, large data visualization, unstructured mesh processing for visualization, volumetric visualization, flow visualization, medical visualization and visualization systems. The book contains more than 350 color illustrations.
We welcome you to the First International Conference on Arts and Technology (ArtsIT 2009), hosted by CSIE of the National Ilan University and co-organized by the National Science Council, ICST, College of EECS at National Ilan University, Software Simulation Society in Taiwan, ISAC, TCA, NCHC, CREATE-NET, and Institute for Information Industry. ArtsIT2009 was held in Yilan, Taiwan, during September 24-25, 2009. The conference comprised the following themes: * New Media Technologies (Evolutionary systems that create arts or display art works, such as tracking sensors, wearable computers, mixed reality, etc. ) * Software Art (Image processing or computer graphics techniques that create arts, including algorithmic art, mathematic art, advanced modeling and rend- ing, etc. ) * Animation Techniques (2D or 3D computer animations, AI-based animations, etc. ) * Multimedia (Integration of different media, such as virtual reality systems, audio, performing arts, etc. ) * Interactive Methods (Vision-based tracking and recognition, interactive art, etc. ) The conference program started with an opening ceremony, followed by three keynote speeches and four technical sessions distributed over a period of two days. Two poster sessions, one hour each, were scheduled before the afternoon oral sessions. An Int- active Arts Exhibition was held in conjunction with ArtsIT 2009. Twelve well-known digital arts teams from Taiwan exhibited 15 artworks in this event, including 10 int- active installation arts, 4 video arts, and 1 digital print. The conference received around 50 submissions from 15 different countries.
With contributions by leading scientists in the field, this book gives the first comprehensive overview of the results of the seminal SmartKom project - one of the most advanced multimodal dialogue systems worldwide.
The application of Computational Intelligence in emerging research areas such as Granular Computing, Mechatronics, and Bioinformatics shows its usefulness often emphasized by Prof Lotfi Zadeh, the inventor of fuzzy logic and many others. This book contains recent advances in Computational Intelligence methods for modeling, optimization and prediction and covers a large number of applications. The book presents new Computational Intelligence theory and methods for modeling and prediction. The range of the various applications is captured with 5 chapters in image processing, 2 chapters in audio processing, 3 chapters in commerce and finance, 2 chapters in communication networks and 6 chapters containing other applications.
As future generation information technology (FGIT) becomes specialized and fr- mented, it is easy to lose sight that many topics in FGIT have common threads and, because of this, advances in one discipline may be transmitted to others. Presentation of recent results obtained in different disciplines encourages this interchange for the advancement of FGIT as a whole. Of particular interest are hybrid solutions that c- bine ideas taken from multiple disciplines in order to achieve something more signi- cant than the sum of the individual parts. Through such hybrid philosophy, a new principle can be discovered, which has the propensity to propagate throughout mul- faceted disciplines. FGIT 2009 was the first mega-conference that attempted to follow the above idea of hybridization in FGIT in a form of multiple events related to particular disciplines of IT, conducted by separate scientific committees, but coordinated in order to expose the most important contributions. It included the following international conferences: Advanced Software Engineering and Its Applications (ASEA), Bio-Science and Bio-Technology (BSBT), Control and Automation (CA), Database Theory and Application (DTA), D- aster Recovery and Business Continuity (DRBC; published independently), Future G- eration Communication and Networking (FGCN) that was combined with Advanced Communication and Networking (ACN), Grid and Distributed Computing (GDC), M- timedia, Computer Graphics and Broadcasting (MulGraB), Security Technology (SecTech), Signal Processing, Image Processing and Pattern Recognition (SIP), and- and e-Service, Science and Technology (UNESST). |
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