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Curvature Scale Space Representation: Theory, Applications, and MPEG-7 Standardization

Curvature Scale Space Representation: Theory, Applications, and MPEG-7 Standardization
Author: F. Mokhtarian
Publisher: Springer Science & Business Media
Total Pages: 444
Release: 2013-11-11
Genre: Computers
ISBN: 9401703434

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MPEG-7 is the first international standard which contains a number of key techniques from Computer Vision and Image Processing. The Curvature Scale Space technique was selected as a contour shape descriptor for MPEG-7 after substantial and comprehensive testing, which demonstrated the superior performance of the CSS-based descriptor. Curvature Scale Space Representation: Theory, Applications, and MPEG-7 Standardization is based on key publications on the CSS technique, as well as its multiple applications and generalizations. The goal was to ensure that the reader will have access to the most fundamental results concerning the CSS method in one volume. These results have been categorized into a number of chapters to reflect their focus as well as content. The book also includes a chapter on the development of the CSS technique within MPEG standardization, including details of the MPEG-7 testing and evaluation processes which led to the selection of the CSS shape descriptor for the standard. The book can be used as a supplementary textbook by any university or institution offering courses in computer and information science.


Combinatorial Image Analysis

Combinatorial Image Analysis
Author: Ralf Reulke
Publisher: Springer
Total Pages: 493
Release: 2006-06-15
Genre: Computers
ISBN: 354035154X

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This volume constitutes the refereed proceedings of the 11th International Workshop on Combinatorial Image Analysis, IWCIA 2006, held in Berlin, June 2006. The book presents 34 revised full papers together with two invited papers, covering topics including combinatorial image analysis; grammars and models for analysis and recognition of scenes and images; combinatorial topology and geometry for images; digital geometry of curves and surfaces; algebraic approaches to image processing, and more.


Scale Space and Variational Methods in Computer Vision

Scale Space and Variational Methods in Computer Vision
Author: Fiorella Sgallari
Publisher: Springer Science & Business Media
Total Pages: 934
Release: 2007-07-23
Genre: Computers
ISBN: 3540728236

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This book constitutes the refereed proceedings of the First International Conference on Scale Space Methods and Variational Methods in Computer Vision, SSVM 2007, emanated from the joint edition of the 4th International Workshop on Variational, Geometric and Level Set Methods in Computer Vision, VLSM 2007 and the 6th International Conference on Scale Space and PDE Methods in Computer Vision, Scale-Space 2007, held in Ischia Italy, May/June 2007.


An Introduction to 3D Computer Vision Techniques and Algorithms

An Introduction to 3D Computer Vision Techniques and Algorithms
Author: Boguslaw Cyganek
Publisher: John Wiley & Sons
Total Pages: 485
Release: 2011-08-10
Genre: Science
ISBN: 1119964474

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Computer vision encompasses the construction of integrated vision systems and the application of vision to problems of real-world importance. The process of creating 3D models is still rather difficult, requiring mechanical measurement of the camera positions or manual alignment of partial 3D views of a scene. However using algorithms, it is possible to take a collection of stereo-pair images of a scene and then automatically produce a photo-realistic, geometrically accurate digital 3D model. This book provides a comprehensive introduction to the methods, theories and algorithms of 3D computer vision. Almost every theoretical issue is underpinned with practical implementation or a working algorithm using pseudo-code and complete code written in C++ and MatLab®. There is the additional clarification of an accompanying website with downloadable software, case studies and exercises. Organised in three parts, Cyganek and Siebert give a brief history of vision research, and subsequently: present basic low-level image processing operations for image matching, including a separate chapter on image matching algorithms; explain scale-space vision, as well as space reconstruction and multiview integration; demonstrate a variety of practical applications for 3D surface imaging and analysis; provide concise appendices on topics such as the basics of projective geometry and tensor calculus for image processing, distortion and noise in images plus image warping procedures. An Introduction to 3D Computer Vision Algorithms and Techniques is a valuable reference for practitioners and programmers working in 3D computer vision, image processing and analysis as well as computer visualisation. It would also be of interest to advanced students and researchers in the fields of engineering, computer science, clinical photography, robotics, graphics and mathematics.


Pattern Recognition and Machine Intelligence

Pattern Recognition and Machine Intelligence
Author: Ashish Ghosh
Publisher: Springer
Total Pages: 693
Release: 2007-11-28
Genre: Computers
ISBN: 3540770461

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This book constitutes the refereed proceedings of the Second International Conference on Pattern Recognition and Machine Intelligence, PReMI 2007, held in Kolkata, India in December 2007. The papers are organized in topical sections on pattern recognition, image analysis, soft computing and applications, data mining and knowledge discovery, bioinformatics, signal and speech processing, document analysis and text mining, biometrics, and video analysis.


Rough Sets, Fuzzy Sets, Data Mining and Granular Computing

Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Author: Hiroshi Sakai
Publisher: Springer Science & Business Media
Total Pages: 539
Release: 2009-11-30
Genre: Computers
ISBN: 3642106455

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Welcome to the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2009), held at the Indian Institute of Technology (IIT), Delhi, India, during December 15-18, 2009. RSFDGrC is a series of conferences spanning over the last 15 years. It investigates the me- ing points among the four major areas outlined in its title. This year, it was co-organized with the Third International Conference on Pattern Recognition and Machine Intelligence (PReMI 2009), which provided additional means for multi-facetedinteractionofboth scientists andpractitioners.Itwasalsothe core component of this year's Rough Set Year in India project. However, it remained a fully international event aimed at building bridges between countries. The ?rst sectin contains the invited papers and a short report on the abo- mentioned project. Let us note that all the RSFDGrC 2009 plenary speakers, Ivo Düntsch, Zbigniew Suraj, Zhongzhi Shi, Sergei Kuznetsov, Qiang Shen, and Yukio Ohsawa, contributed with the full-length articles in the proceedings. The remaining six sections contain 56 regular papers that were selected out of 130 submissions, each peer-reviewed by three PC members. We thank the authors for their high-quality papers submitted to this volume and regret that many deserving papers could not be accepted because of our urge to maintain strict standards. It is worth mentioning that there was quite a good number of papers on the foundations of rough sets and fuzzy sets, many of them authored byIndianresearchers.ThefuzzysettheoryhasbeenpopularinIndiaforalonger time. Now, we can see the rising interest in the rough set theory.


Image Analysis and Recognition

Image Analysis and Recognition
Author: Mohamed Kamel
Publisher: Springer
Total Pages: 1302
Release: 2005-10-10
Genre: Computers
ISBN: 3540319387

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ICIAR 2005, the International Conference on Image Analysis and Recognition, was the second ICIAR conference, and was held in Toronto, Canada. ICIAR is organized annually, and alternates between Europe and North America. ICIAR 2004 was held in Porto, Portugal. The idea of o?ering these conferences came as a result of discussion between researchers in Portugal and Canada to encourage collaboration and exchange, mainly between these two countries, but also with the open participation of other countries, addressing recent advances in theory, methodology and applications. TheresponsetothecallforpapersforICIAR2005wasencouraging.From295 full papers submitted, 153 were ?nally accepted (80 oral presentations, and 73 posters). The review process was carried out by the Program Committee m- bersandotherreviewers;allareexpertsinvariousimageanalysisandrecognition areas. Each paper was reviewed by at least two reviewers, and also checked by the conference co-chairs. The high quality of the papers in these proceedings is attributed ?rst to the authors,and second to the quality of the reviews provided by the experts. We would like to thank the authors for responding to our call, andwewholeheartedlythankthe reviewersfor theirexcellentwork,andfortheir timely response. It is this collective e?ort that resulted in the strong conference program and high-quality proceedings in your hands.


Machine Learning Methods with Noisy, Incomplete or Small Datasets

Machine Learning Methods with Noisy, Incomplete or Small Datasets
Author: Jordi Solé-Casals
Publisher: MDPI
Total Pages: 316
Release: 2021-08-17
Genre: Mathematics
ISBN: 3036512888

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Over the past years, businesses have had to tackle the issues caused by numerous forces from political, technological and societal environment. The changes in the global market and increasing uncertainty require us to focus on disruptive innovations and to investigate this phenomenon from different perspectives. The benefits of innovations are related to lower costs, improved efficiency, reduced risk, and better response to the customers’ needs due to new products, services or processes. On the other hand, new business models expose various risks, such as cyber risks, operational risks, regulatory risks, and others. Therefore, we believe that the entrepreneurial behavior and global mindset of decision-makers significantly contribute to the development of innovations, which benefit by closing the prevailing gap between developed and developing countries. Thus, this Special Issue contributes to closing the research gap in the literature by providing a platform for a scientific debate on innovation, internationalization and entrepreneurship, which would facilitate improving the resilience of businesses to future disruptions. Order Your Print Copy


Advances in Social Computing

Advances in Social Computing
Author: Sun-Ki Chai
Publisher: Springer
Total Pages: 437
Release: 2010-04-08
Genre: Computers
ISBN: 3642120792

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Social computing is concerned with the study of social behavior and social context based on computational systems. Behavioral modeling provides a representation of the social behavior, and allows for experimenting, scenario planning, and deep und- standing of behavior, patterns, and potential outcomes. The pervasive use of computer and Internet technologies by humans in everyday life provides an unprecedented en- ronment of various social activities that, due to the platforms under which they take place, generate large amounts of stored data as a by-product, often in systematically organized form. Social computing facilitates behavioral modeling in model building, analysis, pattern mining, and prediction. Numerous interdisciplinary and interdepe- ent systems are created and used to represent the various social and physical systems for investigating the interactions between groups, communities, or nation-states. This requires joint efforts to take advantage of the state-of-the-art research from multiple disciplines improving social computing and behavioral modeling in order to document lessons learned and develop novel theories, experiments, and methodologies to better explain the interaction between social (both informal and institutionalized), psyc- logical, and physical mechanisms. The goal is to enable us to experiment, create, and recreate an operational environment with a better understanding of the contributions from each individual discipline, forging joint interdisciplinary efforts. This volume comprises the proceedings of the third international workshop on - cial Computing, Behavioral Modeling and Prediction, which has grown trem- dously.


Feature Extraction and Image Processing for Computer Vision

Feature Extraction and Image Processing for Computer Vision
Author: Mark Nixon
Publisher: Academic Press
Total Pages: 650
Release: 2019-11-17
Genre: Computers
ISBN: 0128149779

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Feature Extraction for Image Processing and Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the link between theory and exemplar code of the algorithms." Essential background theory is carefully explained. This text gives students and researchers in image processing and computer vision a complete introduction to classic and state-of-the art methods in feature extraction together with practical guidance on their implementation. The only text to concentrate on feature extraction with working implementation and worked through mathematical derivations and algorithmic methods A thorough overview of available feature extraction methods including essential background theory, shape methods, texture and deep learning Up to date coverage of interest point detection, feature extraction and description and image representation (including frequency domain and colour) Good balance between providing a mathematical background and practical implementation Detailed and explanatory of algorithms in MATLAB and Python