Download or read book How Humans Recognize Objects Segmentation Categorization and Individual Identification written by Chris Fields and published by Frontiers Media SA. This book was released on 2016-08-18 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human beings experience a world of objects: bounded entities that occupy space and persist through time. Our actions are directed toward objects, and our language describes objects. We categorize objects into kinds that have different typical properties and behaviors. We regard some kinds of objects – each other, for example – as animate agents capable of independent experience and action, while we regard other kinds of objects as inert. We re-identify objects, immediately and without conscious deliberation, after days or even years of non-observation, and often following changes in the features, locations, or contexts of the objects being re-identified. Comparative, developmental and adult observations using a variety of approaches and methods have yielded a detailed understanding of object detection and recognition by the visual system and an advancing understanding of haptic and auditory information processing. Many fundamental questions, however, remain unanswered. What, for example, physically constitutes an “object”? How do specific, classically-characterizable object boundaries emerge from the physical dynamics described by quantum theory, and can this emergence process be described independently of any assumptions regarding the perceptual capabilities of observers? How are visual motion and feature information combined to create object information? How are the object trajectories that indicate persistence to human observers implemented, and how are these trajectory representations bound to feature representations? How, for example, are point-light walkers recognized as single objects? How are conflicts between trajectory-driven and feature-driven identifications of objects resolved, for example in multiple-object tracking situations? Are there separate “what” and “where” processing streams for haptic and auditory perception? Are there haptic and/or auditory equivalents of the visual object file? Are there equivalents of the visual object token? How are object-identification conflicts between different perceptual systems resolved? Is the common assumption that “persistent object” is a fundamental innate category justified? How does the ability to identify and categorize objects relate to the ability to name and describe them using language? How are features that an individual object had in the past but does not have currently represented? How are categorical constraints on how objects move or act represented, and how do such constraints influence categorization and the re-identification of individuals? How do human beings re-identify objects, including each other, as persistent individuals across changes in location, context and features, even after gaps in observation lasting months or years? How do human capabilities for object categorization and re-identification over time relate to those of other species, and how do human infants develop these capabilities? What can modeling approaches such as cognitive robotics tell us about the answers to these questions? Primary research reports, reviews, and hypothesis and theory papers addressing questions relevant to the understanding of perceptual object segmentation, categorization and individual identification at any scale and from any experimental or modeling perspective are solicited for this Research Topic. Papers that review particular sets of issues from multiple disciplinary perspectives or that advance integrative hypotheses or models that take data from multiple experimental approaches into account are especially encouraged.
Download or read book How Humans Recognize Objects Segmentation Categorization and Individual Identification written by and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human beings experience a world of objects: bounded entities that occupy space and persist through time. Our actions are directed toward objects, and our language describes objects. We categorize objects into kinds that have different typical properties and behaviors. We regard some kinds of objects - each other, for example - as animate agents capable of independent experience and action, while we regard other kinds of objects as inert. We re-identify objects, immediately and without conscious deliberation, after days or even years of non-observation, and often following changes in the features, locations, or contexts of the objects being re-identified. Comparative, developmental and adult observations using a variety of approaches and methods have yielded a detailed understanding of object detection and recognition by the visual system and an advancing understanding of haptic and auditory information processing. Many fundamental questions, however, remain unanswered. What, for example, physically constitutes an "object"? How do specific, classically-characterizable object boundaries emerge from the physical dynamics described by quantum theory, and can this emergence process be described independently of any assumptions regarding the perceptual capabilities of observers? How are visual motion and feature information combined to create object information? How are the object trajectories that indicate persistence to human observers implemented, and how are these trajectory representations bound to feature representations? How, for example, are point-light walkers recognized as single objects? How are conflicts between trajectory-driven and feature-driven identifications of objects resolved, for example in multiple-object tracking situations? Are there separate "what" and "where" processing streams for haptic and auditory perception? Are there haptic and/or auditory equivalents of the visual object file? Are there equivalents of the visual object token? How are object-identification conflicts between different perceptual systems resolved? Is the common assumption that "persistent object" is a fundamental innate category justified? How does the ability to identify and categorize objects relate to the ability to name and describe them using language? How are features that an individual object had in the past but does not have currently represented? How are categorical constraints on how objects move or act represented, and how do such constraints influence categorization and the re-identification of individuals? How do human beings re-identify objects, including each other, as persistent individuals across changes in location, context and features, even after gaps in observation lasting months or years? How do human capabilities for object categorization and re-identification over time relate to those of other species, and how do human infants develop these capabilities? What can modeling approaches such as cognitive robotics tell us about the answers to these questions? Primary research reports, reviews, and hypothesis and theory papers addressing questions relevant to the understanding of perceptual object segmentation, categorization and individual identification at any scale and from any experimental or modeling perspective are solicited for this Research Topic. Papers that review particular sets of issues from multiple disciplinary perspectives or that advance integrative hypotheses or models that take data from multiple experimental approaches into account are especially encouraged.
Download or read book Object Categorization written by Axel Pinz and published by Now Publishers Inc. This book was released on 2006 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: This article presents foundations, original research and trends in the field of object categorization by computer vision methods. The research goals in object categorization are to detect objects in images and to determine the object's categories. Categorization aims for the recognition of generic classes of objects, and thus has also been termed 'generic object recognition'. This is in contrast to the recognition of specific, individual objects. While humans are usually better in generic than in specific recognition, categorization is much harder to achieve for today's computer architectures.
Download or read book Deep Learning for Computer Vision written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2019-04-04 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.
Download or read book Practical Machine Learning for Computer Vision written by Valliappa Lakshmanan and published by "O'Reilly Media, Inc.". This book was released on 2021-07-21 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability. Google engineers Valliappa Lakshmanan, Martin Görner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras. You'll learn how to: Design ML architecture for computer vision tasks Select a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your task Create an end-to-end ML pipeline to train, evaluate, deploy, and explain your model Preprocess images for data augmentation and to support learnability Incorporate explainability and responsible AI best practices Deploy image models as web services or on edge devices Monitor and manage ML models
Download or read book Computer Vision ECCV 2008 written by David Forsyth and published by Springer Science & Business Media. This book was released on 2008-10-07 with total page 911 pages. Available in PDF, EPUB and Kindle. Book excerpt: The four-volume set comprising LNCS volumes 5302/5303/5304/5305 constitutes the refereed proceedings of the 10th European Conference on Computer Vision, ECCV 2008, held in Marseille, France, in October 2008. The 243 revised papers presented were carefully reviewed and selected from a total of 871 papers submitted. The four books cover the entire range of current issues in computer vision. The papers are organized in topical sections on recognition, stereo, people and face recognition, object tracking, matching, learning and features, MRFs, segmentation, computational photography and active reconstruction.
Download or read book Object Recognition Of Digital Images In Wavelet Neural Network written by Arul Murugan R and published by Archers & Elevators Publishing House. This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Object Categorization written by Sven J. Dickinson and published by Cambridge University Press. This book was released on 2009-09-07 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique multidisciplinary perspective on the problem of visual object categorization.
Download or read book Visual Object Recognition written by Kristen Grauman and published by Morgan & Claypool Publishers. This book was released on 2011 with total page 184 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 Encyclopedia of Perception written by E. Bruce Goldstein and published by SAGE. This book was released on 2009-10-15 with total page 1281 pages. Available in PDF, EPUB and Kindle. Book excerpt: Because of the ease with which we perceive, many people see perception as something that "just happens." However, even seemingly simple perceptual experiences involve complex underlying mechanisms, which are often hidden from our conscious experience. These mechanisms are being investigated by researchers and theorists in fields such as psychology, cognitive science, neuroscience, computer science, and philosophy. A few examples of the questions posed by these investigations are, What do infants perceive? How does perception develop? What do perceptual disorders reveal about normal functioning? How can information from one sense, such as hearing, be affected by information from another sense, such as vision? How is the information from all of our senses combined to result in our perception of a coherent environment? What are some practical outcomes of basic research in perception? These are just a few of the questions this encyclopedia will consider, as it presents a comprehensive overview of the field of perception for students, researchers, and professionals in psychology, the cognitive sciences, neuroscience, and related medical disciplines such as neurology and ophthalmology.
Download or read book Healthcare Industry 4 0 written by P. Karthikeyan and published by CRC Press. This book was released on 2023-08-28 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers computer vision-based applications in digital healthcare industry 4.0, including different computer vision techniques, image classification, image segmentations, and object detection. Various application case studies from domains such as science, engineering, and social networking are introduced, along with their architecture and how they leverage various technologies, such as edge computing and cloud computing. It also covers applications of computer vision in tumor detection, cancer detection, combating COVID-19, and patient monitoring. Features: Provides a state-of-the-art computer vision application in the digital health care industry Reviews advances in computer vision and data science technologies for analyzing information on human function and disability Includes practical implementation of computer vision application using recent tools and software Explores computer vision-enabled medical/clinical data security in the cloud Includes case studies from the leading computer vision integrated vendors like Amazon, Microsoft, IBM, and Google This book is aimed at researchers and graduate students in bioengineering, intelligent systems, and computer science and engineering.
Download or read book Cognitive Vision Systems written by Henrik I. Christensen and published by Springer. This book was released on 2006-06-29 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a post-event proceedings volume and contains selected papers based on the presentations given, and the lively discussions that ensued, during a seminar held in Dagstuhl Castle, Germany, in October 2003. Co-sponsored by ECVision, the cognitive vision network of excellence, it was organized to further strengthen cooperation between research groups from different countries working in the field of cognitive vision systems.
Download or read book Intelligent Systems written by João Carlos Xavier-Junior and published by Springer Nature. This book was released on 2022-11-18 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 13653 and 13654 constitutes the refereed proceedings of the 11th Brazilian Conference on Intelligent Systems, BRACIS 2022, which took place in Campinas, Brazil, in November/December 2022. The 89 papers presented in the proceedings were carefully reviewed and selected from 225 submissions. The conference deals with theoretical aspects and applications of artificial and computational intelligence.
Download or read book Intelligent Systems and Human Machine Collaboration written by Siddhartha Bhattacharyya and published by Springer Nature. This book was released on 2023-03-29 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book constitutes proceedings of the International Conference on Intelligent Systems and Human-Machine Collaboration 2022. The papers consist of research from different domains of human-machine interaction, computer engineering like quantum computational intelligence, big data analytics, the Internet of things, etc. The book includes significant contributions from academia and industry dealing with human-machine interaction both from the theoretical development and the application point of view. It also brings out research articles in interdisciplinary platforms applying human-machine interaction. The book is useful to researchers and practitioners alike.
Download or read book Computational Intelligence in Pattern Recognition written by Asit Kumar Das and published by Springer. This book was released on 2019-08-17 with total page 1046 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents practical development experiences in different areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.
Download or read book Shape Perception in Human and Computer Vision written by Sven J. Dickinson and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive and authoritative text/reference presents a unique, multidisciplinary perspective on Shape Perception in Human and Computer Vision. Rather than focusing purely on the state of the art, the book provides viewpoints from world-class researchers reflecting broadly on the issues that have shaped the field. Drawing upon many years of experience, each contributor discusses the trends followed and the progress made, in addition to identifying the major challenges that still lie ahead. Topics and features: examines each topic from a range of viewpoints, rather than promoting a specific paradigm; discusses topics on contours, shape hierarchies, shape grammars, shape priors, and 3D shape inference; reviews issues relating to surfaces, invariants, parts, multiple views, learning, simplicity, shape constancy and shape illusions; addresses concepts from the historically separate disciplines of computer vision and human vision using the same “language” and methods.
Download or read book From Animals to Robots and Back Reflections on Hard Problems in the Study of Cognition written by Jeremy L. Wyatt and published by Springer. This book was released on 2014-07-10 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cognitive Science is a discipline that brings together research in natural and artificial systems and this is clearly reflected in the diverse contributions to From Animals to Robots and Back. In tribute to Aaron Sloman and his pioneering work in Cognitive Science and Artificial Intelligence, the editors have collected a unique collection of cross-disciplinary papers that include work on: · intelligent robotics; · philosophy of cognitive science; · emotional research · computational vision; · comparative psychology; and · human-computer interaction. Key themes such as the importance of taking an architectural view in approaching cognition, run through the text. Drawing on the expertize of leading international researchers, contemporary debates in the study of natural and artificial cognition are addressed from complementary and contrasting perspectives with key issues being outlined at various levels of abstraction. From Animals to Robots and Back, will give readers with backgrounds in the study of both natural and artificial cognition an important window on the state of the art in cognitive systems research.
