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Computer Vision -- ACCV 2014: 12th Asian Conference on Computer Vision, Singapore, Singapore, November 1-5, 2014, Revised Selected Papers, Part I (Lecture Notes in Computer Science #9003)
by Daniel Cremers Ian Reid Hideo Saito Ming-Hsuan YangThe five-volume set LNCS 9003--9007 constitutes the thoroughly refereed post-conference proceedings of the 12th Asian Conference on Computer Vision, ACCV 2014, held in Singapore, Singapore, in November 2014. The total of 227 contributions presented in these volumes was carefully reviewed and selected from 814 submissions. The papers are organized in topical sections on recognition; 3D vision; low-level vision and features; segmentation; face and gesture, tracking; stereo, physics, video and events; and poster sessions 1-3.
Computer Vision -- ACCV 2014: 12th Asian Conference on Computer Vision, Singapore, Singapore, November 1-5, 2014, Revised Selected Papers, Part III (Lecture Notes in Computer Science #9005)
by Daniel Cremers Ian Reid Hideo Saito Ming-Hsuan YangThe five-volume set LNCS 9003--9007 constitutes the thoroughly refereed post-conference proceedings of the 12th Asian Conference on Computer Vision, ACCV 2014, held in Singapore, Singapore, in November 2014. The total of 227 contributions presented in these volumes was carefully reviewed and selected from 814 submissions. The papers are organized in topical sections on recognition; 3D vision; low-level vision and features; segmentation; face and gesture, tracking; stereo, physics, video and events; and poster sessions 1-3.
Computer Vision -- ACCV 2014: 12th Asian Conference on Computer Vision, Singapore, Singapore, November 1-5, 2014, Revised Selected Papers, Part IV (Lecture Notes in Computer Science #9006)
by Daniel Cremers Ian Reid Hideo Saito Ming-Hsuan YangThe five-volume set LNCS 9003--9007 constitutes the thoroughly refereed post-conference proceedings of the 12th Asian Conference on Computer Vision, ACCV 2014, held in Singapore, Singapore, in November 2014. The total of 227 contributions presented in these volumes was carefully reviewed and selected from 814 submissions. The papers are organized in topical sections on recognition; 3D vision; low-level vision and features; segmentation; face and gesture, tracking; stereo, physics, video and events; and poster sessions 1-3.
Computer Vision Applications: Third Workshop, WCVA 2018, Held in Conjunction with ICVGIP 2018, Hyderabad, India, December 18, 2018, Revised Selected Papers (Communications in Computer and Information Science #1019)
by Chetan Arora Kaushik MitraThis book constitutes the refereed proceedings of the third Workshop on Computer Vision Applications, WCVA 2018, held in Conjunction with ICVGIP 2018, in Hyderabad, India, in December 2018. The 10 revised full papers presented were carefully reviewed and selected from 32 submissions. The papers focus on computer vision; industrial applications; medical applications; and social applications.
Computer Vision Metrics: Survey, Taxonomy, and Analysis
by Scott KrigBased on the successful 2014 book published by Apress, this textbook edition is expanded to provide a comprehensive history and state-of-the-art survey for fundamental computer vision methods. With over 800 essential references, as well as chapter-by-chapter learning assignments, both students and researchers can dig deeper into core computer vision topics. The survey covers everything from feature descriptors, regional and global feature metrics, feature learning architectures, deep learning, neuroscience of vision, neural networks, and detailed example architectures to illustrate computer vision hardware and software optimization methods. To complement the survey, the textbook includes useful analyses which provide insight into the goals of various methods, why they work, and how they may be optimized. The text delivers an essential survey and a valuable taxonomy, thus providing a key learning tool for students, researchers and engineers, to supplement the many effective hands-on resources and open source projects, such as OpenCVand other imaging and deep learning tools.
Computer Vision Metrics: Survey, Taxonomy, and Analysis of Computer Vision, Visual Neuroscience, and Visual AI
by Scott KrigThis 2nd Edition, based on the successful 2016 textbook, has been updated and expanded to cover 3rd generation Computer Vision and AI as it supersedes historical visual computing methods, providing a comprehensive survey of essential topics and methods in Computer Vision. With over 1,200 essential references, as well as chapter-by-chapter learning assignments, the book offers a valuable resource for students, researchers, scientists and engineers, helping them dig deeper into core computer vision and foundational visual computing and neuroscience topics. As before, a historical survey of advances in Computer Vision is provided, updated to reflect the latest methods such as Vision Transformers, attention models, alternative features such as Fourier neurons and Binary neurons, hybrid DNN architectures, self-supervised and enhanced learning models, Associative Multimodal Learning, Continuous Learning, View Synthesis, intelligent Scientific Imaging, andadvances in training protocols. Updates have also been added for 2d/3d cameras, software libraries and open source resources, computer vision cloud services, and vision/AI hardware accelerators. Discussion and analysis are provided to uncover intuition and delve into the essence of key advancements, applied and forward-looking topics.
Computer Vision Metrics: Textbook Edition
by Scott KrigBased on the successful 2014 book published by Apress, this textbook edition is expanded to provide a comprehensive history and state-of-the-art survey for fundamental computer vision methods. With over 800 essential references, as well as chapter-by-chapter learning assignments, both students and researchers can dig deeper into core computer vision topics. The survey covers everything from feature descriptors, regional and global feature metrics, feature learning architectures, deep learning, neuroscience of vision, neural networks, and detailed example architectures to illustrate computer vision hardware and software optimization methods. To complement the survey, the textbook includes useful analyses which provide insight into the goals of various methods, why they work, and how they may be optimized. The text delivers an essential survey and a valuable taxonomy, thus providing a key learning tool for students, researchers and engineers, to supplement the many effective hands-on resources and open source projects, such as OpenCVand other imaging and deep learning tools.
Computer Vision Projects with OpenCV and Python 3: Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow
by Matthew ReverGain a working knowledge of advanced machine learning and explore Python's powerful tools for extracting data from images and videos Key Features Implement image classification and object detection using machine learning and deep learning Perform image classification, object detection, image segmentation, and other Computer Vision tasks Crisp content with a practical approach to solving real-world problems in Computer Vision Book Description Python is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems. With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features,and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google's Tesseract software, and tracking human body poses using DeeperCut within TensorFlow. By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries. What you will learn Install and run major Computer Vision packages within Python Apply powerful support vector machines for simple digit classification Understand deep learning with TensorFlow Build a deep learning classifier for general images Use LSTMs for automated image captioning Read text from real-world images Extract human pose data from images Who this book is for Python programmers and machine learning developers who wish to build exciting Computer Vision projects using the power of machine learning and OpenCV will find this book useful. The only prerequisite for this book is that you should have a sound knowledge of Python programming.
Computer Vision Projects with PyTorch: Design and Develop Production-Grade Models
by Akshay Kulkarni Adarsha Shivananda Nitin Ranjan SharmaDesign and develop end-to-end, production-grade computer vision projects for real-world industry problems. This book discusses computer vision algorithms and their applications using PyTorch.The book begins with the fundamentals of computer vision: convolutional neural nets, RESNET, YOLO, data augmentation, and other regularization techniques used in the industry. And then it gives you a quick overview of the PyTorch libraries used in the book. After that, it takes you through the implementation of image classification problems, object detection techniques, and transfer learning while training and running inference. The book covers image segmentation and an anomaly detection model. And it discusses the fundamentals of video processing for computer vision tasks putting images into videos. The book concludes with an explanation of the complete model building process for deep learning frameworks using optimized techniques with highlights on model AI explainability.After reading this book, you will be able to build your own computer vision projects using transfer learning and PyTorch.What You Will LearnSolve problems in computer vision with PyTorch.Implement transfer learning and perform image classification, object detection, image segmentation, and other computer vision applicationsDesign and develop production-grade computer vision projects for real-world industry problemsInterpret computer vision models and solve business problemsWho This Book Is ForData scientists and machine learning engineers interested in building computer vision projects and solving business problems
Computer Vision Systems: 10th International Conference, ICVS 2015, Copenhagen, Denmark, July 6-9, 2015, Proceedings (Lecture Notes in Computer Science #9163)
by Volker Krüger Lazaros Nalpantidis Jan-Olof Eklundh Antonios GasteratosThis book constitutes the refereed proceedings of the 10th International Conference on Computer Vision Systems, ICVS 2015, held in Copenhagen, Denmark, in July 2015. The 48 papers presented were carefully reviewed and selected from 92 submissions. The paper are organized in topical sections on biological and cognitive vision; hardware-implemented and real-time vision systems; high-level vision; learning and adaptation; robot vision; and vision systems applications.
Computer Vision Systems: 11th International Conference, ICVS 2017, Shenzhen, China, July 10-13, 2017, Revised Selected Papers (Lecture Notes in Computer Science #10528)
by Ming Liu Haoyao Chen Markus VinczeIn the past few years, with the advances in microelectronics and digital te- nology, cameras became a widespread media. This, along with the enduring increase in computing power boosted the development of computer vision s- tems. The International Conference on Computer Vision Systems (ICVS) covers the advances in this area. This is to say that ICVS is not and should not be yet another computer vision conference. The ?eld of computer vision is fully covered by many well-established and famous conferences and ICVS di?ers from these by covering the systems point of view. ICVS 2008 was the 6th International Conference dedicated to advanced research on computer vision systems. The conference, continuing a series of successful events in Las Palmas, Vancouver, Graz, New York and Bielefeld, in 2008 was held on Santorini. In all, 128 papers entered the review process and each was reviewed by three independent reviewers using the double-blind review method. Of these, 53 - pers were accepted (23 as oral and 30 as poster presentation). There were also two invited talks by P. Anandan and by Heinrich H. Bultho ¨ ?. The presented papers cover all aspects of computer vision systems, namely: cognitive vision, monitor and surveillance, computer vision architectures, calibration and reg- tration, object recognition and tracking, learning, human--machine interaction and cross-modal systems.
Computer Vision Systems: 12th International Conference, ICVS 2019, Thessaloniki, Greece, September 23–25, 2019, Proceedings (Lecture Notes in Computer Science #11754)
by Markus Vincze Dimitrios Tzovaras Dimitrios Giakoumis Antonis ArgyrosThis book constitutes the refereed proceedings of the 12th International Conference on Computer Vision Systems, ICVS 2019, held in Thessaloniki, Greece, in September 2019.The 72 papers presented were carefully reviewed and selected from 114 submissions. The papers are organized in the following topical sections; hardware accelerated and real time vision systems; robotic vision; vision systems applications; high-level and learning vision systems; cognitive vision systems; movement analytics and gesture recognition for human-machine collaboration in industry; cognitive and computer vision assisted systems for energy awareness and behavior analysis; and vision-enabled UAV and counter UAV technologies for surveillance and security of critical infrastructures.
Computer Vision Systems: 13th International Conference, ICVS 2021, Virtual Event, September 22-24, 2021, Proceedings (Lecture Notes in Computer Science #12899)
by Lazaros Nalpantidis Ming Liu Markus Vincze Timothy Patten Henrik I ChristensenThis book constitutes the refereed proceedings of the 13th International Conference on Computer Vision Systems, ICVS 2021, held in September 2021. Due to COVID-19 pandemic the conference was held virtually. The 20 papers presented were carefully reviewed and selected from 29 submissions. cover a broad spectrum of issues falling under the wider scope of computer vision in real-world applications, including among others, vision systems for robotics, autonomous vehicles, agriculture and medicine. In this volume, the papers are organized into the sections: attention systems; classification and detection; semantic interpretation; video and motion analysis; computer vision systems in agriculture.
Computer Vision Systems: 14th International Conference, ICVS 2023, Vienna, Austria, September 27–29, 2023, Proceedings (Lecture Notes in Computer Science #14253)
by Peter Corke Henrik I. Christensen Markus Vincze Renaud Detry Jean-Baptiste WeibelThis volume LNCS 14253 constitutes the refereed proceedings of the 14th International Conference, ICVS 2023, in Vienna, Austria, in September 2023.. The 37 full papers presented were carefully reviewed and selected from 74 submissions. The conference focuses on Humans and Hands; Medical and Health Care; Farming and Forestry; Automation and Manufacturing; Mobile Robotics and Autonomous Systems; and Performance and Robustness.
Computer Vision Techniques for the Diagnosis of Skin Cancer (Series in BioEngineering)
by M. Emre Celebi Jacob ScharcanskiThe goal of this volume is to summarize the state-of-the-art in the utilization of computer vision techniques in the diagnosis of skin cancer. Malignant melanoma is one of the most rapidly increasing cancers in the world. Early diagnosis is particularly important since melanoma can be cured with a simple excision if detected early. In recent years, dermoscopy has proved valuable in visualizing the morphological structures in pigmented lesions. However, it has also been shown that dermoscopy is difficult to learn and subjective. Newer technologies such as infrared imaging, multispectral imaging, and confocal microscopy, have recently come to the forefront in providing greater diagnostic accuracy. These imaging technologies presented in this book can serve as an adjunct to physicians and provide automated skin cancer screening. Although computerized techniques cannot as yet provide a definitive diagnosis, they can be used to improve biopsy decision-making as well as early melanoma detection, especially for patients with multiple atypical nevi.
Computer Vision Using Deep Learning: Neural Network Architectures with Python and Keras
by Vaibhav VerdhanOrganizations spend huge resources in developing software that can perform the way a human does. Image classification, object detection and tracking, pose estimation, facial recognition, and sentiment estimation all play a major role in solving computer vision problems. This book will bring into focus these and other deep learning architectures and techniques to help you create solutions using Keras and the TensorFlow library. You'll also review mutliple neural network architectures, including LeNet, AlexNet, VGG, Inception, R-CNN, Fast R-CNN, Faster R-CNN, Mask R-CNN, YOLO, and SqueezeNet and see how they work alongside Python code via best practices, tips, tricks, shortcuts, and pitfalls. All code snippets will be broken down and discussed thoroughly so you can implement the same principles in your respective environments.Computer Vision Using Deep Learning offers a comprehensive yet succinct guide that stitches DL and CV together to automate operations, reduce human intervention, increase capability, and cut the costs. What You'll LearnExamine deep learning code and concepts to apply guiding principals to your own projectsClassify and evaluate various architectures to better understand your options in various use casesGo behind the scenes of basic deep learning functions to find out how they workWho This Book Is ForProfessional practitioners working in the fields of software engineering and data science. A working knowledge of Python is strongly recommended. Students and innovators working on advanced degrees in areas related to computer vision and Deep Learning.
Computer Vision Using Local Binary Patterns: Computer Vision Using Local Binary Patterns (Computational Imaging and Vision #40)
by Guoying Zhao Matti Pietikäinen Timo Ahonen Abdenour HadidThe recent emergence of Local Binary Patterns (LBP) has led to significant progress in applying texture methods to various computer vision problems and applications. The focus of this research has broadened from 2D textures to 3D textures and spatiotemporal (dynamic) textures. Also, where texture was once utilized for applications such as remote sensing, industrial inspection and biomedical image analysis, the introduction of LBP-based approaches have provided outstanding results in problems relating to face and activity analysis, with future scope for face and facial expression recognition, biometrics, visual surveillance and video analysis. Computer Vision Using Local Binary Patterns provides a detailed description of the LBP methods and their variants both in spatial and spatiotemporal domains. This comprehensive reference also provides an excellent overview as to how texture methods can be utilized for solving different kinds of computer vision and image analysis problems. Source codes of the basic LBP algorithms, demonstrations, some databases and a comprehensive LBP bibliography can be found from an accompanying web site. Topics include: local binary patterns and their variants in spatial and spatiotemporal domains, texture classification and segmentation, description of interest regions, applications in image retrieval and 3D recognition - Recognition and segmentation of dynamic textures, background subtraction, recognition of actions, face analysis using still images and image sequences, visual speech recognition and LBP in various applications. Written by pioneers of LBP, this book is an essential resource for researchers, professional engineers and graduate students in computer vision, image analysis and pattern recognition. The book will also be of interest to all those who work with specific applications of machine vision.
Computer Vision and Audition in Urban Analysis Using the Remorph Framework (Studies in Systems, Decision and Control #192)
by Mohammad Ali Nematollahi Samaneh Shahbazi Nashid NabianArtificial Intelligence (AI) is penetrating in all sciences as a multidisciplinary approach. However, adopting the theory of AI including computer vision and computer audition to urban intellectual space, is always difficult for architecture and urban planners. This book overcomes this challenge through a conceptual framework by merging computer vision and audition to urban studies based on a series of workshops called Remorph, conducted by Tehran Urban Innovation Center (TUIC).
Computer Vision and Augmented Reality in iOS: OpenCV and ARKit Applications
by Ahmed Fathi BekhitLearn how computer vision works, how augmented reality renders digital graphics into the physical world via an iPhone’s camera, and how to incorporate these technologies into your own apps. This book shows you how to take full advantage of computer vision technologies.Interacting with other people online usually involves user-generated images and videos; whether it be “memes”, short videos, or heavily-modified images. Before smart phones, generating this content required a professional using high-level image and video editing software. Not any more. This book will teach you to use computer vision in the most popular ways, such as for facial recognition, image to text analysis and, of course, recording a video of a dancing hot dog in your living room. Starting with the history of computer vision, image and video processing fundamentals, and an introduction to developing augmented reality applications, you’ll learn to incorporate computer vision both in the content you create and the apps you develop for end users. Computer Vision and Augmented Reality in iOS reveals how every user with access to the Internet and a smart phone can easily generate heavily-modified images and videos. What You'll LearnIncorporate mathematics related to computer vision into your appsHost computer vision models remotely for mobile useImplement visual-inertial state estimation algorithms for mobile augmented realityWho This Book Is ForProfessionals or post graduate students in software development or engineering who have a basic understanding of how software development works and are interested in implementing computer vision into their development. It's recommended that readers already have a working knowledge of C++ and Swift.
Computer Vision and Graphics: International Conference, ICCVG 2016, Warsaw, Poland, September 19-21, 2016, Proceedings (Lecture Notes in Computer Science #9972)
by Leszek J. Chmielewski Amitava Datta Ryszard Kozera Konrad WojciechowskiThis book constitutes the thoroughly refereed post-conference proceedings of the International Conference on Computer Vision and Graphics, ICCVG 2008, held in Warsaw, Poland, in November 2008. The 48 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on image processing, image quality assessment, geometrical models of objects and scenes, motion analysis, visual navigation and active vision, image and video coding, virtual reality and multimedia applications, biomedical applications, practical applications of pattern recognition, computer animation, visualization and graphical data presentation.
Computer Vision and Graphics: International Conference, ICCVG 2020, Warsaw, Poland, September 14–16, 2020, Proceedings (Lecture Notes in Computer Science #12334)
by Leszek J. Chmielewski Ryszard Kozera Arkadiusz OrłowskiThis book constitutes the refereed proceedings of the International Conference on Computer Vision and Graphics, ICCVG 2020, held in Warsaw, Poland, in September 2020. The 20 full papers were selected from 49 submissions. The contributions cover topics such as: modelling of human visual perception; computational geometry; geometrical models of objects and scenes; illumination and reflection models and methods; image formation; image and video coding; image filtering and enhancement; biomedical image processing; biomedical graphics; colour image processing; multispectral image processing; pattern recognition in image processing; scene understanding; motion analysis, visual navigation and active vision; human motion detection and analysis; visualisation and graphical data presentation; hardware and architectures for image processing; computer-aided graphic design; 3D imaging, shading and rendering; computer animation; graphics for internet and mobile systems; virtual reality; image and video databases; digital watermarking; multimedia applications; and computer art. Due to the Corona pandemic ICCVG 2020 was held as a virtual event.
Computer Vision and Graphics: International Conference, Iccvg 2014, Warsaw, Poland, September 15-17, 2014, Proceedings (Lecture Notes in Computer Science #8671)
by Nicolai Petkov Leszek J. Chmielewski Ryszard Kozera Konrad Wojciechowski Alfred M. Bruckstein Arkadiusz OrłowskiThis book constitutes the refereed proceedings of the International Conference on Computer Vision and Graphics, ICCVG 2018, held in Warsaw, Poland, in September 2018. The 45 full papers were selected from 117 submissions. The contributions are thematically arranged as follows: computer graphics, image quality and graphic, user interfaces, object classification and features, 3D and stereo image processing, low-level and middle-level image processing, medical image analysis, motion analysis and tracking, security and protection, pattern recognition and new concepts in classification.
Computer Vision and Graphics: Proceedings of the International Conference on Computer Vision and Graphics ICCVG 2022 (Lecture Notes in Networks and Systems #598)
by Leszek J. Chmielewski Arkadiusz OrłowskiThis book contains 17 papers presented at the conference devoted to cutting-edge technologies and concepts related to image processing. A broad collection of problems including man–machine interfaces, comparison of quantum and conventional computing in deep learning, medical image processing, image segmentation, face recognition, outdoor scene analysis, image rendering and colorization, map generation, traffic analysis, hardware acceleration, data association, and visual cryptography is investigated.Research on these issues is important, among others due to that large amounts of video data are collected continually. They can be easily stored, but their analysis is still a challenge.The book is primarily intended for researchers and practitioners in image analysis and generation, as well as for students in the fields related to computer science. However, any reader interested in the subject matter of the book will find some chapters interesting and valuable.
Computer Vision and Image Analysis for Industry 4.0
by Nazmul Siddique Mohammad Shamsul Arefin Ahad, Md Atiqur Rahman Dewan, M. Ali AkberComputer vision and image analysis are indispensable components of every automated environment. Modern machine vision and image analysis techniques play key roles in automation and quality assurance. Working environments can be improved significantly if we integrate computer vision and image analysis techniques. The more advancement in innovation and research in computer vision and image processing, the greater the efficiency of machines as well as humans. Computer Vision and Image Analysis for Industry 4.0 focuses on the roles of computer vision and image analysis for 4.0 IR-related technologies. The text proposes a variety of techniques for disease detection and prediction, text recognition and signature verification, image captioning, flood level assessment, crops classifications and fabrication of smart eye-controlled wheelchairs.
Computer Vision and Image Processing: 4th International Conference, CVIP 2019, Jaipur, India, September 27–29, 2019, Revised Selected Papers, Part I (Communications in Computer and Information Science #1147)
by Balasubramanian Raman Neeta Nain Santosh Kumar VipparthiThis two-volume set (CCIS 1147, CCIS 1148) constitutes the refereed proceedings of the 4th International Conference on Computer Vision and Image Processing. held in Jaipur, India, in September 2019. The 73 full papers and 10 short papers were carefully reviewed and selected from 202 submissions. The papers are organized according to the following topics: Part I: Biometrics; Computer Forensic; Computer Vision; Dimension Reduction; Healthcare Information Systems; Image Processing; Image segmentation; Information Retrieval; Instance based learning; Machine Learning.Part II: Neural Network; Object Detection; Object Recognition; Online Handwriting Recognition; Optical Character Recognition; Security and Privacy; Unsupervised Clustering.