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Computer Vision in Control Systems-4: Real Life Applications (Intelligent Systems Reference Library #136)
by Margarita N. Favorskaya Lakhmi C. JainThe research book is a continuation of the authors’ previous works, which are focused on recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms.The book gathers selected contributions addressing a number of real-life applications including the identification of handwritten texts, watermarking techniques, simultaneous localization and mapping for mobile robots, motion control systems for mobile robots, analysis of indoor human activity, facial image quality assessment, android device controlling, processing medical images, clinical decision-making and foot progression angle detection.Given the tremendous interest among researchers in the development and applications of computer vision paradigms in the field of business, engineering, medicine, security and aviation, the book offers a timely guide for all PhD students, professors, researchers and software developers working in the areas of digital video processing and computer vision technologies.
Computer Vision in Control Systems—6: Advances in Practical Applications (Intelligent Systems Reference Library #182)
by Margarita N. Favorskaya Lakhmi C. JainThis book attempts to improve algorithms by novel theories and complex data analysis in different scopes including object detection, remote sensing, data transmission, data fusion, gesture recognition, and edical image processing and analysis.The book is directed to the Ph.D. students, professors, researchers, and software developers working in the areas of digital video processing and computer vision technologies.
Computer Vision in Human-Computer Interaction: ECCV 2006 Workshop on HCI, Graz, Austria, May 13, 2006, Proceedings (Lecture Notes in Computer Science #3979)
by Thomas S. Huang Nicu Sebe Michael S. Lew Vladimir Pavlovic Mathias Kölsch Aphrodite Galata Branislav KisacaninThis book constitutes the refereed proceedings of the International Workshop on Human-Computer Interaction, HCI/ECCV 2006. The 11 revised full papers presented were carefully reviewed and selected from 27 submissions. The papers address a wide range of theoretical and application issues in human-computer interaction ranging from face analysis, gesture and emotion recognition, and event detection to various applications in those fields.
Computer Vision in Human-Computer Interaction: ICCV 2005 Workshop on HCI, Beijing, China, October 21, 2005, Proceedings (Lecture Notes in Computer Science #3766)
by Nicu Sebe Michael S. Lew Thomas S. HuangHuman-Computer Interaction (HCI) lies at the crossroads of many scienti?c areas including arti?cial intelligence, computer vision, face recognition, motion tracking, etc. In order for HCI systems to interact seamlessly with people, they need to understand their environment through vision and auditory input. Mo- over, HCI systems should learn how to adaptively respond depending on the situation. The goal of this workshop was to bring together researchers from the ?eld of computer vision whose work is related to human-computer interaction. The selected articles for this workshop address a wide range of theoretical and - plication issues in human-computer interaction ranging from human-robot - teraction, gesture recognition, and body tracking, to facial features analysis and human-computer interaction systems. This year 74 papers from 18 countries were submitted and 22 were accepted for presentation at the workshop after being reviewed by at least 3 members of the Program Committee. We had therefore a very competitive acceptance rate of less than 30% and as a consequence we had a very-high-quality workshop. Wewouldliketo thankallmembersofthe ProgramCommitteefor their help in ensuring the quality of the papers accepted for publication. We are grateful to Dr. Jian Wang for giving the keynote address. In addition, we wish to thank the organizers of the 10th IEEE International Conference on Computer Vision and our sponsors, University of Amsterdam, Leiden Institute of Advanced Computer Science, and the University of Illinois at Urbana-Champaign, for support in setting up our workshop.
Computer Vision in Human-Computer Interaction: ECCV 2004 Workshop on HCI, Prague, Czech Republic, May 16, 2004, Proceedings (Lecture Notes in Computer Science #3058)
by Nicu Sebe Michael S. Lew Thomas S. HuangThis book constitutes the refereed proceedings of the International Workshop on Human-Computer Interaction, HCI 2004, held at ECCV 2004 in Prague, Czech Republic in May 2004. The 19 revised full papers presented together with an introductory overview and an invited paper were carefully reviewed and selected from 45 submissions. The papers are organized in topical sections on human-robot interaction, gesture recognition and body tracking, systems, and face and head.
Computer Vision in Sports (Advances in Computer Vision and Pattern Recognition)
by Thomas B. Moeslund Graham Thomas Adrian HiltonThe first book of its kind devoted to this topic, this comprehensive text/reference presents state-of-the-art research and reviews current challenges in the application of computer vision to problems in sports. Opening with a detailed introduction to the use of computer vision across the entire life-cycle of a sports event, the text then progresses to examine cutting-edge techniques for tracking the ball, obtaining the whereabouts and pose of the players, and identifying the sport being played from video footage. The work concludes by investigating a selection of systems for the automatic analysis and classification of sports play. The insights provided by this pioneering collection will be of great interest to researchers and practitioners involved in computer vision, sports analysis and media production.
Computer Vision in the Infrared Spectrum: Challenges and Approaches (Synthesis Lectures on Computer Vision)
by Michael Teutsch Angel D. Sappa Riad I. HammoudHuman visual perception is limited to the visual-optical spectrum. Machine vision is not. Cameras sensitive to the different infrared spectra can enhance the abilities of autonomous systems and visually perceive the environment in a holistic way. Relevant scene content can be made visible especially in situations, where sensors of other modalities face issues like a visual-optical camera that needs a source of illumination. As a consequence, not only human mistakes can be avoided by increasing the level of automation, but also machine-induced errors can be reduced that, for example, could make a self-driving car crash into a pedestrian under difficult illumination conditions. Furthermore, multi-spectral sensor systems with infrared imagery as one modality are a rich source of information and can provably increase the robustness of many autonomous systems. Applications that can benefit from utilizing infrared imagery range from robotics to automotive and from biometrics to surveillance. In this book, we provide a brief yet concise introduction to the current state-of-the-art of computer vision and machine learning in the infrared spectrum. Based on various popular computer vision tasks such as image enhancement, object detection, or object tracking, we first motivate each task starting from established literature in the visual-optical spectrum. Then, we discuss the differences between processing images and videos in the visual-optical spectrum and the various infrared spectra. An overview of the current literature is provided together with an outlook for each task. Furthermore, available and annotated public datasets and common evaluation methods and metrics are presented. In a separate chapter, popular applications that can greatly benefit from the use of infrared imagery as a data source are presented and discussed. Among them are automatic target recognition, video surveillance, or biometrics including face recognition. Finally, we conclude with recommendations for well-fitting sensor setups and data processing algorithms for certain computer vision tasks. We address this book to prospective researchers and engineers new to the field but also to anyone who wants to get introduced to the challenges and the approaches of computer vision using infrared images or videos. Readers will be able to start their work directly after reading the book supported by a highly comprehensive backlog of recent and relevant literature as well as related infrared datasets including existing evaluation frameworks. Together with consistently decreasing costs for infrared cameras, new fields of application appear and make computer vision in the infrared spectrum a great opportunity to face nowadays scientific and engineering challenges.
Computer Vision in Vehicle Technology: Land, Sea, and Air
by Antonio M. López Atsushi Imiya Tomas Pajdla Jose M. ÁlvarezA unified view of the use of computer vision technology for different types of vehicles Computer Vision in Vehicle Technology focuses on computer vision as on-board technology, bringing together fields of research where computer vision is progressively penetrating: the automotive sector, unmanned aerial and underwater vehicles. It also serves as a reference for researchers of current developments and challenges in areas of the application of computer vision, involving vehicles such as advanced driver assistance (pedestrian detection, lane departure warning, traffic sign recognition), autonomous driving and robot navigation (with visual simultaneous localization and mapping) or unmanned aerial vehicles (obstacle avoidance, landscape classification and mapping, fire risk assessment). The overall role of computer vision for the navigation of different vehicles, as well as technology to address on-board applications, is analysed. Key features: Presents the latest advances in the field of computer vision and vehicle technologies in a highly informative and understandable way, including the basic mathematics for each problem. Provides a comprehensive summary of the state of the art computer vision techniques in vehicles from the navigation and the addressable applications points of view. Offers a detailed description of the open challenges and business opportunities for the immediate future in the field of vision based vehicle technologies. This is essential reading for computer vision researchers, as well as engineers working in vehicle technologies, and students of computer vision.
Computer Vision in Vehicle Technology: Land, Sea, and Air
by Antonio M. López Atsushi Imiya Tomas Pajdla Jose M. ÁlvarezA unified view of the use of computer vision technology for different types of vehicles Computer Vision in Vehicle Technology focuses on computer vision as on-board technology, bringing together fields of research where computer vision is progressively penetrating: the automotive sector, unmanned aerial and underwater vehicles. It also serves as a reference for researchers of current developments and challenges in areas of the application of computer vision, involving vehicles such as advanced driver assistance (pedestrian detection, lane departure warning, traffic sign recognition), autonomous driving and robot navigation (with visual simultaneous localization and mapping) or unmanned aerial vehicles (obstacle avoidance, landscape classification and mapping, fire risk assessment). The overall role of computer vision for the navigation of different vehicles, as well as technology to address on-board applications, is analysed. Key features: Presents the latest advances in the field of computer vision and vehicle technologies in a highly informative and understandable way, including the basic mathematics for each problem. Provides a comprehensive summary of the state of the art computer vision techniques in vehicles from the navigation and the addressable applications points of view. Offers a detailed description of the open challenges and business opportunities for the immediate future in the field of vision based vehicle technologies. This is essential reading for computer vision researchers, as well as engineers working in vehicle technologies, and students of computer vision.
Computer Vision & Laser Vibrometry, Volume 6: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023 (Conference Proceedings of the Society for Experimental Mechanics Series)
by Javad Baqersad Dario Di MaioComputer Vision & Laser Vibrometry, Volume 6: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics, 2023, the sixth volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Computer Vision, Laser Vibrometry and Structural Health Monitoring, including papers on:Novel TechniquesOptical Methods,Scanning LDV MethodsPhotogrammetry & DICStructural Health Monitoring
Computer Vision Methods for Fast Image Classification and Retrieval (Studies in Computational Intelligence #821)
by Rafał SchererThe book presents selected methods for accelerating image retrieval and classification in large collections of images using what are referred to as ‘hand-crafted features.’ It introduces readers to novel rapid image description methods based on local and global features, as well as several techniques for comparing images.Developing content-based image comparison, retrieval and classification methods that simulate human visual perception is an arduous and complex process. The book’s main focus is on the application of these methods in a relational database context. The methods presented are suitable for both general-type and medical images. Offering a valuable textbook for upper-level undergraduate or graduate-level courses on computer science or engineering, as well as a guide for computer vision researchers, the book focuses on techniques that work under real-world large-dataset conditions.
Computer Vision Metrics: Survey, Taxonomy, and Analysis
by Scott KrigComputer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors actually work, how they are designed, with observations about tuning the methods for achieving robustness and invariance targets for specific applications. The survey is broader than it is deep, with over 540 references provided to dig deeper. The taxonomy includes search methods, spectra components, descriptor representation, shape, distance functions, accuracy, efficiency, robustness and invariance attributes, and more. Rather than providing ‘how-to’ source code examples and shortcuts, this book provides a counterpoint discussion to the many fine opencv community source code resources available for hands-on practitioners.
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 and deep learning. 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 and deep learning architectures. 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 OpenCV and other imaging and deep learning tools.
Computer Vision, Pattern Recognition, Image Processing, and Graphics: 7th National Conference, NCVPRIPG 2019, Hubballi, India, December 22–24, 2019, Revised Selected Papers (Communications in Computer and Information Science #1249)
by R. Venkatesh Babu Mahadeva Prasanna Vinay P. NamboodiriThis book constitutes the refereed proceedings of the 7th National Conference on Computer Vision, Pattern Recognition, Image Processing, and Graphics, NCVPRIPG 2019, held in Hubballi, India, in December 2019.The 55 revised full papers 3 short papers presented in this volume were carefully reviewed and selected from 210 submissions. The papers are organized in topical sections on vision and geometry, learning and vision, image processing and document analysis, detection and recognition.
Computer Vision, Pattern Recognition, Image Processing, and Graphics: 6th National Conference, NCVPRIPG 2017, Mandi, India, December 16-19, 2017, Revised Selected Papers (Communications in Computer and Information Science #841)
by Renu Rameshan Chetan Arora Sumantra Dutta RoyThis book constitutes the refereed proceedings of the 6th National Conference on Computer Vision, Pattern Recognition, Image Processing, and Graphics, NCVPRIPG 2017, held in Mandi, India, in December 2017. The 48 revised full papers presented in this volume were carefully reviewed and selected from 147 submissions. The papers are organized in topical sections on video processing; image and signal processing; segmentation, retrieval, captioning; pattern recognition applications.
Computer Vision Projects with OpenCV and Python 3: Six End-to-end Projects Built Using Machine Learning With Opencv, Python, And Tensorflow
by Matthew ReverThis book demonstrates techniques to leverage the power of Python, OpenCV, and TensorFlow to solve problems in Computer Vision. This book also shows you how to build an application that can estimate human poses within images. You will also classify images and identify humans in videos, and then develop your own handwritten digit classifier.
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: 9th International Conference, ICVS 2013, St. Petersburg, Russia, July 16-18, 2013. Proceedings (Lecture Notes in Computer Science #7963)
by Mei Chen Bastian Leibe Bernd NeumannThis book constitutes the refereed proceedings of the 9th International Conference on Computer Vision Systems, ICVS 2013, held in St. Petersburg, Russia, July 16-18, 2013. Proceedings. The 16 revised papers presented with 20 poster papers were carefully reviewed and selected from 94 submissions. The papers are organized in topical sections on image and video capture; visual attention and object detection; self-localization and pose estimation; motion and tracking; 3D reconstruction; features, learning and validation.
Computer Vision Systems: First International Conference, ICVS '99 Las Palmas, Gran Canaria, Spain, January 13-15, 1999 Proceedings (Lecture Notes in Computer Science #1542)
by Henrik I. ChristensenComputer Vision has now reached a level of maturity that allows us not only to perform research on individual methods but also to build fully integrated computer vision systems of a signi cant complexity. This opens up a number of new problems related to architectures, systems integration, validation of - stems using benchmarking techniques, and so on. So far, the majority of vision conferences have focused on component technologies, which has motivated the organization of the First International Conference on Computer Vision Systems (ICVS). It is our hope that the conference will allow us not only to see a number of interesting new vision techniques and systems but hopefully also to de ne the research issues that need to be addressed to pave the way for more wide-scale use of computer vision in a diverse set of real-world applications. ICVS is organized as a single-track conference consisting of high-quality, p- viously unpublished, contributed papers on new and original research on c- puter vision systems. All contributions will be presented orally. A total of 65 papers were submitted for consideration by the conference. All papers were - viewed by three reviewers from the program committee. Thirty-two of the papers were selected for presentation. ICVS’99 is being held at the Alfredo Kraus Auditorium and Convention Centre, in Las Palmas, on the lovely Canary Islands, Spain. The setting is spri- like, which seems only appropriate as the basis for a new conference.
Computer Vision Systems: 14th International Conference, ICVS 2023, Vienna, Austria, September 27–29, 2023, Proceedings (Lecture Notes in Computer Science #14253)
by Henrik I. Christensen Peter Corke Renaud Detry Jean-Baptiste Weibel Markus VinczeThis 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 Systems: 8th International Conference, ICVS 2011, Sophia Antipolis, France, September 20-22, 2011, Proceedings (Lecture Notes in Computer Science #6962)
by James L. Crowley Bruce Draper Monique ThonnatThis book constitutes the refereed proceedings of the 8th International Conference on Computer Vision Systems, ICVS 2011, held in Sophia Antipolis, France, in September 2009. The 22 revised papers presented were carefully reviewed and selected from 58 submissions. The papers are organized in topical sections on vision systems, control of perception, performance evaluation, activity recognition, and knowledge directed vision.
Computer Vision Systems: Third International Conference, ICVS 2003, Graz, Austria, April 1-3, 2003, Proceedings (Lecture Notes in Computer Science #2626)
by James Crowley Justus Piater Markus Vincze Lucas PalettaThis book constitutes the refereed proceedings of the Third International Conference on Computer Vision Systems, ICVS 2003, held in Graz, Austria, in April 2003. The 51 revised full papers presented were carefully reviewed and selected from 109 submissions. The papers are organized in topical sections on cognitive vision, philosophical issues in cognitive vision, cognitive vision and applications, computer vision architectures, performance evaluation, implementation methods, architecture and classical computer vision, and video annotation.
Computer Vision Systems: 7th International Conference on Computer Vision Systems, ICVS 2009 Liège, Belgium, October 13-15, 2009, Proceedings (Lecture Notes in Computer Science #5815)
by Mario Fritz Bernt Schiele Justus H. PiaterThis book constitutes the refereed proceedings of the 7th International Conference on Computer Vision Systems, ICVS 2009, held in Liege, Belgium, October 13-15, 2009. The 21 papers for oral presentation presented together with 24 poster presentations and 2 invited papers were carefully reviewed and selected from 96 submissions. The papers are organized in topical sections on human-machine-interaction, sensors, features and representations, stereo, 3D and optical flow, calibration and registration, mobile and autonomous systems, evaluation, studies and applications, learning, recognition and adaption.
Computer Vision Systems: 6th International Conference on Computer Vision Systems, ICVS 2008 Santorini, Greece, May 12-15, 2008, Proceedings (Lecture Notes in Computer Science #5008)
by Antonios Gasteratos Markus Vincze John K. TsotsosIn 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: 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 VinczeThis book constitutes the refereed proceedings of the 11th International Conference on Computer Vision Systems, ICVS 2017, held in Shenzhen, China, in July 2017. The 61 papers presented were carefully reviewed and selected from 92 submissions. The papers are organized in topical sections on visual control, visual navigation, visual inspection, image processing, human robot interaction, stereo system, image retrieval, visual detection, visual recognition, system design, and 3D vision / fusion.