Download or read book Advances in Object Recognition Systems written by Ioannis Kypraios and published by BoD – Books on Demand. This book was released on 2012-05-09 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: An invariant object recognition system needs to be able to recognise the object under any usual a priori defined distortions such as translation, scaling and in-plane and out-of-plane rotation. Ideally, the system should be able to recognise (detect and classify) any complex scene of objects even within background clutter noise. In this book, we present recent advances towards achieving fully-robust object recognition. The relation and importance of object recognition in the cognitive processes of humans and animals is described as well as how human- and animal-like cognitive processes can be used for the design of biologically-inspired object recognition systems. Colour processing is discussed in the development of fully-robust object recognition systems. Examples of two main categories of object recognition systems, the optical correlators and pure artificial neural network architectures, are given. Finally, two examples of object recognition's applications are described in details. With the recent technological advancements object recognition becomes widely popular with existing applications in medicine for the study of human learning and memory, space science and remote sensing for image analysis, mobile computing and augmented reality, semiconductors industry, robotics and autonomous mobile navigation, public safety and urban management solutions and many more others. This book is a "must-read" for everyone with a core or wider interest in this "hot" area of cutting-edge research.
Download or read book Object Recognition written by M. Bennamoun and published by Springer Science & Business Media. This book was released on 2001-12-12 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatie object recognition is a multidisciplinary research area using con cepts and tools from mathematics, computing, optics, psychology, pattern recognition, artificial intelligence and various other disciplines. The purpose of this research is to provide a set of coherent paradigms and algorithms for the purpose of designing systems that will ultimately emulate the functions performed by the Human Visual System (HVS). Hence, such systems should have the ability to recognise objects in two or three dimensions independently of their positions, orientations or scales in the image. The HVS is employed for tens of thousands of recognition events each day, ranging from navigation (through the recognition of landmarks or signs), right through to communication (through the recognition of characters or people themselves). Hence, the motivations behind the construction of recognition systems, which have the ability to function in the real world, is unquestionable and would serve industrial (e.g. quality control), military (e.g. automatie target recognition) and community needs (e.g. aiding the visually impaired). Scope, Content and Organisation of this Book This book provides a comprehensive, yet readable foundation to the field of object recognition from which research may be initiated or guided. It repre sents the culmination of research topics that I have either covered personally or in conjunction with my PhD students. These areas include image acqui sition, 3-D object reconstruction, object modelling, and the matching of ob jects, all of which are essential in the construction of an object recognition system.
Download or read book An Introduction to Object Recognition written by Marco Alexander Treiber and published by Springer Science & Business Media. This book was released on 2010-07-23 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rapid development of computer hardware has enabled usage of automatic object recognition in an increasing number of applications, ranging from industrial image processing to medical applications, as well as tasks triggered by the widespread use of the internet. Each area of application has its specific requirements, and consequently these cannot all be tackled appropriately by a single, general-purpose algorithm. This easy-to-read text/reference provides a comprehensive introduction to the field of object recognition (OR). The book presents an overview of the diverse applications for OR and highlights important algorithm classes, presenting representative example algorithms for each class. The presentation of each algorithm describes the basic algorithm flow in detail, complete with graphical illustrations. Pseudocode implementations are also included for many of the methods, and definitions are supplied for terms which may be unfamiliar to the novice reader. Supporting a clear and intuitive tutorial style, the usage of mathematics is kept to a minimum. Topics and features: presents example algorithms covering global approaches, transformation-search-based methods, geometrical model driven methods, 3D object recognition schemes, flexible contour fitting algorithms, and descriptor-based methods; explores each method in its entirety, rather than focusing on individual steps in isolation, with a detailed description of the flow of each algorithm, including graphical illustrations; explains the important concepts at length in a simple-to-understand style, with a minimum usage of mathematics; discusses a broad spectrum of applications, including some examples from commercial products; contains appendices discussing topics related to OR and widely used in the algorithms, (but not at the core of the methods described in the chapters). Practitioners of industrial image processing will find this simple introduction and overview to OR a valuable reference, as will graduate students in computer vision courses. Marco Treiber is a software developer at Siemens Electronics Assembly Systems, Munich, Germany, where he is Technical Lead in Image Processing for the Vision System of SiPlace placement machines, used in SMT assembly.
Download or read book Advances in Object Recognition Systems written by and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Object Recognition written by M. Bennamoun and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatie object recognition is a multidisciplinary research area using con cepts and tools from mathematics, computing, optics, psychology, pattern recognition, artificial intelligence and various other disciplines. The purpose of this research is to provide a set of coherent paradigms and algorithms for the purpose of designing systems that will ultimately emulate the functions performed by the Human Visual System (HVS). Hence, such systems should have the ability to recognise objects in two or three dimensions independently of their positions, orientations or scales in the image. The HVS is employed for tens of thousands of recognition events each day, ranging from navigation (through the recognition of landmarks or signs), right through to communication (through the recognition of characters or people themselves). Hence, the motivations behind the construction of recognition systems, which have the ability to function in the real world, is unquestionable and would serve industrial (e.g. quality control), military (e.g. automatie target recognition) and community needs (e.g. aiding the visually impaired). Scope, Content and Organisation of this Book This book provides a comprehensive, yet readable foundation to the field of object recognition from which research may be initiated or guided. It repre sents the culmination of research topics that I have either covered personally or in conjunction with my PhD students. These areas include image acqui sition, 3-D object reconstruction, object modelling, and the matching of ob jects, all of which are essential in the construction of an object recognition system.
Download or read book Visual Object Recognition written by Kristen Gauman and published by Morgan & Claypool Publishers. This book was released on 2010-10-10 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: The visual recognition problem is central to computer vision research. From robotics to information retrieval, many desired applications demand the ability to identify and localize categories, places, and objects. This tutorial overviews computer vision algorithms for visual object recognition and image classification. We introduce primary representations and learning approaches, with an emphasis on recent advances in the field. The target audience consists of researchers or students working in AI, robotics, or vision who would like to understand what methods and representations are available for these problems. This lecture summarizes what is and isn't possible to do reliably today, and overviews key concepts that could be employed in systems requiring visual categorization. Table of Contents: Introduction / Overview: Recognition of Specific Objects / Local Features: Detection and Description / Matching Local Features / Geometric Verification of Matched Features / Example Systems: Specific-Object Recognition / Overview: Recognition of Generic Object Categories / Representations for Object Categories / Generic Object Detection: Finding and Scoring Candidates / Learning Generic Object Category Models / Example Systems: Generic Object Recognition / Other Considerations and Current Challenges / Conclusions
Download or read book Three Dimensional Object Recognition Systems written by Anil K Jain and published by . This book was released on 1993-05-05 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: The design and construction of three-dimensional [3-D] object recognition systems has long occupied the attention of many computer vision researchers. The variety of systems that have been developed for this task is evidence both of its strong appeal to researchers and its applicability to modern manufacturing, industrial, military, and consumer environments. 3-D object recognition is of interest to scientists and engineers in several different disciplines due to both a desire to endow computers with robust visual capabilities, and the wide applications which would benefit from mature and robust vision systems. However, 3-D object recognition is a very complex problem, and few systems have been developed for actual production use; most existing systems have been developed for experimental use by researchers only. This edited collection of papers summarizes the state of the art in 3-D object recognition using examples of existing 3-D systems developed by leading researchers in the field. While most chapters describe a complete object recognition system, chapters on biological vision, sensing, and early processing are also included. The volume will serve as a valuable reference source for readers who are involved in implementing model-based object recognition systems, stimulating the cross-fertilisation of ideas in the various domains. The variety of topics on Image Communication is so broad that no one can be a specialist in all the topics, and the whole area is beyond the scope of a single volume, while the requirement of up to date information is ever increasing. This new closed-end book series is intended both as a comprehensive reference for those already active in the area of Image Communication, as well as providing newcomers with a foothold for commencing research. Each volume will comprise a state of the art work on the editor's/author's area of expertise, containing information until now scattered in many journals and proceedings.
Download or read book Advanced Topics in Computer Vision written by Giovanni Maria Farinella and published by Springer Science & Business Media. This book was released on 2013-09-24 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a broad selection of cutting-edge research, covering both theoretical and practical aspects of reconstruction, registration, and recognition. The text provides an overview of challenging areas and descriptions of novel algorithms. Features: investigates visual features, trajectory features, and stereo matching; reviews the main challenges of semi-supervised object recognition, and a novel method for human action categorization; presents a framework for the visual localization of MAVs, and for the use of moment constraints in convex shape optimization; examines solutions to the co-recognition problem, and distance-based classifiers for large-scale image classification; describes how the four-color theorem can be used for solving MRF problems; introduces a Bayesian generative model for understanding indoor environments, and a boosting approach for generalizing the k-NN rule; discusses the issue of scene-specific object detection, and an approach for making temporal super resolution video.
Download or read book Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches written by Chiranji Lal Chowdhary and published by Computing and Networks. This book was released on 2021-11 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by a team of International experts, this edited book covers state-of-the-art research in the fields of computer vision and recognition systems from fundamental concepts to methodologies and technologies and real-world applications. The book will be useful for industry and academic researchers, scientists and engineers.
Download or read book Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition Emerging Research and Opportunities written by Chakraborty, Shouvik and published by IGI Global. This book was released on 2020-03-13 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision and object recognition are two technological methods that are frequently used in various professional disciplines. In order to maintain high levels of quality and accuracy of services in these sectors, continuous enhancements and improvements are needed. The implementation of artificial intelligence and machine learning has assisted in the development of digital imaging, yet proper research on the applications of these advancing technologies is lacking. Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition: Emerging Research and Opportunities explores the theoretical and practical aspects of modern advancements in digital image analysis and object detection as well as its applications within healthcare, security, and engineering fields. Featuring coverage on a broad range of topics such as disease detection, adaptive learning, and automated image segmentation, this book is ideally designed for engineers, physicians, researchers, academicians, practitioners, scientists, industry professionals, scholars, and students seeking research on the current developments in object recognition using artificial intelligence.
Download or read book Advancement of Deep Learning and its Applications in Object Detection and Recognition written by Roohie Naaz Mir and published by CRC Press. This book was released on 2023-05-10 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Object detection is a basic visual identification problem in computer vision that has been explored extensively over the years. Visual object detection seeks to discover objects of specific target classes in a given image with pinpoint accuracy and apply a class label to each object instance. Object recognition strategies based on deep learning have been intensively investigated in recent years as a result of the remarkable success of deep learning-based image categorization. In this book, we go through in detail detector architectures, feature learning, proposal generation, sampling strategies, and other issues that affect detection performance. The book describes every newly proposed novel solution but skips through the fundamentals so that readers can see the field's cutting edge more rapidly. Moreover, unlike prior object detection publications, this project analyses deep learning-based object identification methods systematically and exhaustively, and also gives the most recent detection solutions and a collection of noteworthy research trends. The book focuses primarily on step-by-step discussion, an extensive literature review, detailed analysis and discussion, and rigorous experimentation results. Furthermore, a practical approach is displayed and encouraged.
Download or read book Deep Learning in Object Recognition Detection and Segmentation written by Xiaogang Wang and published by . This book was released on 2016 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: As a major breakthrough in artificial intelligence, deep learning has achieved very impressive success in solving grand challenges in many fields including speech recognition, natural language processing, computer vision, image and video processing, and multimedia. This article provides a historical overview of deep learning and focus on its applications in object recognition, detection, and segmentation, which are key challenges of computer vision and have numerous applications to images and videos. The discussed research topics on object recognition include image classification on ImageNet, face recognition, and video classification. The detection part covers general object detection on ImageNet, pedestrian detection, face landmark detection (face alignment), and human landmark detection (pose estimation). On the segmentation side, the article discusses the most recent progress on scene labeling, semantic segmentation, face parsing, human parsing and saliency detection. Object recognition is considered as whole-image classification, while detection and segmentation are pixelwise classification tasks. Their fundamental differences will be discussed in this article. Fully convolutional neural networks and highly efficient forward and backward propagation algorithms specially designed for pixelwise classification task will be introduced. The covered application domains are also much diversified. Human and face images have regular structures, while general object and scene images have much more complex variations in geometric structures and layout. Videos include the temporal dimension. Therefore, they need to be processed with different deep models. All the selected domain applications have received tremendous attentions in the computer vision and multimedia communities. Through concrete examples of these applications, we explain the key points which make deep learning outperform conventional computer vision systems. (1) Different than traditional pattern recognition systems, which heavily rely on manually designed features, deep learning automatically learns hierarchical feature representations from massive training data and disentangles hidden factors of input data through multi-level nonlinear mappings. (2) Different than existing pattern recognition systems which sequentially design or train their key components, deep learning is able to jointly optimize all the components and crate synergy through close interactions among them. (3) While most machine learning models can be approximated with neural networks with shallow structures, for some tasks, the expressive power of deep models increases exponentially as their architectures go deep. Deep models are especially good at learning global contextual feature representation with their deep structures. (4) Benefitting from the large learning capacity of deep models, some classical computer vision challenges can be recast as high-dimensional data transform problems and can be solved from new perspectives. Finally, some open questions and future works regarding to deep learning in object recognition, detection, and segmentation will be discussed.
Download or read book Three Dimensional Object Recognition from Range Images written by Minsoo Suk and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Science Workbench is a monograph series which will provide you with an in-depth working knowledge of current developments in computer technology. Every volume in this series will deal with a topic of importance in computer science and elaborate on how you yourself can build systems related to the main theme. You will be able to develop a variety of systems, including computer software tools, computer graphics, computer animation, database management systems, and computer-aided design and manufacturing systems. Computer Science Workbench represents an important new contribution in the field of practical computer technology. T08iyasu L. Kunii PREFACE The primary aim of this book is to present a coherent and self-contained de scription of recent advances in three-dimensional object recognition from range images. Three-dimensional object recognition concerns recognition and localiza tion of objects of interest in a scene from input images. This problem is one of both theoretical and practical importance. On the theoretical side, it is an ideal vehicle for the study of the general area of computer vision since it deals with several important issues encountered in computer vision-for example, issues such as feature extraction, acquisition, representation and proper use of knowl edge, employment of efficient control strategies, coupling numerical and symbolic computations, and parallel implementation of algorithms. On the practical side, it has a wide range of applications in areas such as robot vision, autonomous navigation, automated inspection of industrial parts, and automated assembly.
Download or read book Advancements in Computer Vision Applications in Intelligent Systems and Multimedia Technologies written by Muhammad Sarfraz and published by Engineering Science Reference. This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book discusses innovative developments in computational imaging for solving real-life issues and problems and addresses their execution in various disciplines"--
Download or read book Progress in Computer Recognition Systems written by Robert Burduk and published by Springer. This book was released on 2019-05-07 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights recent research on computer recognition systems, one of the most promising directions in artificial intelligence. Offering the most comprehensive study on this field to date, it gathers 36 carefully selected articles contributed by experts on pattern recognition. Presenting recent research on methodology and applications, the book offers a valuable reference tool for scientists whose work involves designing computer pattern recognition systems. Its target audience also includes researchers and students in computer science, artificial intelligence, and robotics.
Download or read book Advancements in Computer Vision and Image Processing written by Garcia-Rodriguez, Jose and published by IGI Global. This book was released on 2018-04-06 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in computer vision and image processing has grown in recent years with the advancement of everyday technologies such as smartphones, computer games, and social robotics. These advancements have allowed for advanced algorithms that have improved the processing capabilities of these technologies. Advancements in Computer Vision and Image Processing is a critical scholarly resource that explores the impact of new technologies on computer vision and image processing methods in everyday life. Featuring coverage on a wide range of topics including 3D visual localization, cellular automata-based structures, and eye and face recognition, this book is geared toward academicians, technology professionals, engineers, students, and researchers seeking current research on the development of sophisticated algorithms to process images and videos in real time.
Download or read book Object Detection by Stereo Vision Images written by R. Arokia Priya and published by John Wiley & Sons. This book was released on 2022-09-14 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: OBJECT DETECTION BY STEREO VISION IMAGES Since both theoretical and practical aspects of the developments in this field of research are explored, including recent state-of-the-art technologies and research opportunities in the area of object detection, this book will act as a good reference for practitioners, students, and researchers. Current state-of-the-art technologies have opened up new opportunities in research in the areas of object detection and recognition of digital images and videos, robotics, neural networks, machine learning, stereo vision matching algorithms, soft computing, customer prediction, social media analysis, recommendation systems, and stereo vision. This book has been designed to provide directions for those interested in researching and developing intelligent applications to detect an object and estimate depth. In addition to focusing on the performance of the system using high-performance computing techniques, a technical overview of certain tools, languages, libraries, frameworks, and APIs for developing applications is also given. More specifically, detection using stereo vision images/video from its developmental stage up till today, its possible applications, and general research problems relating to it are covered. Also presented are techniques and algorithms that satisfy the peculiar needs of stereo vision images along with emerging research opportunities through analysis of modern techniques being applied to intelligent systems. Audience Researchers in information technology looking at robotics, deep learning, machine learning, big data analytics, neural networks, pattern & data mining, and image and object recognition. Industrial sectors include automotive electronics, security and surveillance systems, and online retailers.
