How Humans Recognize Objects Segmentation Categorization And Individual Identification

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How Humans Recognize Objects: Segmentation, Categorization and Individual Identification

Author : Chris Fields
Publisher : Frontiers Media SA
Page : 267 pages
File Size : 49,9 Mb
Release : 2016-08-18
Category : Psychology
ISBN : 9782889199402

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How Humans Recognize Objects: Segmentation, Categorization and Individual Identification by Chris Fields Pdf

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.

How Humans Recognize Objects: Segmentation, Categorization and Individual Identification

Author : Anonim
Publisher : Unknown
Page : 0 pages
File Size : 49,8 Mb
Release : 2016
Category : Electronic
ISBN : OCLC:1368414176

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How Humans Recognize Objects: Segmentation, Categorization and Individual Identification by Anonim Pdf

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.

Object Categorization

Author : Sven J. Dickinson
Publisher : Cambridge University Press
Page : 553 pages
File Size : 51,9 Mb
Release : 2009-09-07
Category : Computers
ISBN : 9780521887380

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Object Categorization by Sven J. Dickinson Pdf

A unique multidisciplinary perspective on the problem of visual object categorization.

Object Categorization

Author : Axel Pinz
Publisher : Now Publishers Inc
Page : 110 pages
File Size : 49,9 Mb
Release : 2006
Category : Computers
ISBN : 9781933019130

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Object Categorization by Axel Pinz Pdf

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.

Computer Vision - ECCV 2008

Author : David Forsyth,Philip Torr,Andrew Zisserman
Publisher : Springer
Page : 891 pages
File Size : 50,5 Mb
Release : 2008-10-11
Category : Computers
ISBN : 9783540886938

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Computer Vision - ECCV 2008 by David Forsyth,Philip Torr,Andrew Zisserman Pdf

Welcome to the 2008EuropeanConference onComputer Vision. These proce- ings are the result of a great deal of hard work by many people. To produce them, a total of 871 papers were reviewed. Forty were selected for oral pres- tation and 203 were selected for poster presentation, yielding acceptance rates of 4.6% for oral, 23.3% for poster, and 27.9% in total. Weappliedthreeprinciples.First,sincewehadastronggroupofAreaChairs, the ?nal decisions to accept or reject a paper rested with the Area Chair, who wouldbeinformedbyreviewsandcouldactonlyinconsensuswithanotherArea Chair. Second, we felt that authors were entitled to a summary that explained how the Area Chair reached a decision for a paper. Third, we were very careful to avoid con?icts of interest. Each paper was assigned to an Area Chair by the Program Chairs, and each Area Chair received a pool of about 25 papers. The Area Chairs then identi?ed and rankedappropriatereviewersfor eachpaper in their pool, and a constrained optimization allocated three reviewers to each paper. We are very proud that every paper received at least three reviews. At this point, authors were able to respond to reviews. The Area Chairs then needed to reach a decision. We used a series of procedures to ensure careful review and to avoid con?icts of interest. ProgramChairs did not submit papers. The Area Chairs were divided into three groups so that no Area Chair in the group was in con?ict with any paper assigned to any Area Chair in the group.

Object Recognition Of Digital Images In Wavelet Neural Network

Author : Arul Murugan R
Publisher : Archers & Elevators Publishing House
Page : 128 pages
File Size : 54,8 Mb
Release : 2024-06-10
Category : Antiques & Collectibles
ISBN : 9789386501240

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Object Recognition Of Digital Images In Wavelet Neural Network by Arul Murugan R Pdf

Visual Object Recognition

Author : Kristen Grauman,Bastian Leibe
Publisher : Morgan & Claypool Publishers
Page : 184 pages
File Size : 51,9 Mb
Release : 2011
Category : Computers
ISBN : 9781598299687

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Visual Object Recognition by Kristen Grauman,Bastian Leibe Pdf

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

Encyclopedia of Perception

Author : E. Bruce Goldstein
Publisher : SAGE
Page : 1281 pages
File Size : 43,5 Mb
Release : 2009-10-15
Category : Psychology
ISBN : 9781412940818

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Encyclopedia of Perception by E. Bruce Goldstein Pdf

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.

Deep Learning for Computer Vision

Author : Jason Brownlee
Publisher : Machine Learning Mastery
Page : 564 pages
File Size : 48,8 Mb
Release : 2019-04-04
Category : Computers
ISBN : 8210379456XXX

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Deep Learning for Computer Vision by Jason Brownlee Pdf

Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.

Intelligent Systems

Author : João Carlos Xavier-Junior,Ricardo Araújo Rios
Publisher : Springer Nature
Page : 686 pages
File Size : 40,5 Mb
Release : 2022-11-18
Category : Computers
ISBN : 9783031216893

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Intelligent Systems by João Carlos Xavier-Junior,Ricardo Araújo Rios Pdf

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.

Healthcare Industry 4.0

Author : P. Karthikeyan,Polinpapilinho F. Katina,R. Rajagopal
Publisher : CRC Press
Page : 186 pages
File Size : 50,6 Mb
Release : 2023-08-28
Category : Technology & Engineering
ISBN : 9781000930573

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Healthcare Industry 4.0 by P. Karthikeyan,Polinpapilinho F. Katina,R. Rajagopal Pdf

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.

Cognitive Vision Systems

Author : Henrik I. Christensen,Hans-Hellmut Nagel
Publisher : Springer
Page : 372 pages
File Size : 40,8 Mb
Release : 2006-06-29
Category : Computers
ISBN : 9783540339724

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Cognitive Vision Systems by Henrik I. Christensen,Hans-Hellmut Nagel Pdf

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.

Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction

Author : Friedhelm Schwenker,Stefan Scherer,Louis-Philippe Morency
Publisher : Springer
Page : 145 pages
File Size : 51,7 Mb
Release : 2015-01-03
Category : Computers
ISBN : 9783319148991

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Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction by Friedhelm Schwenker,Stefan Scherer,Louis-Philippe Morency Pdf

This book constitutes the thoroughly refereed post-workshop proceedings of the Third IAPR TC3 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2014, held in Stockholm, Sweden, in August 2014, as a satellite event of the International Conference on Pattern Recognition, ICPR 2014. The 14 revised papers presented focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition, user identification, and recognition of human activities.

Computer Vision – ECCV 2012

Author : Andrew Fitzgibbon,Svetlana Lazebnik,Pietro Perona,Yoichi Sato,Cordelia Schmid
Publisher : Springer
Page : 881 pages
File Size : 50,5 Mb
Release : 2012-09-26
Category : Computers
ISBN : 9783642337185

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Computer Vision – ECCV 2012 by Andrew Fitzgibbon,Svetlana Lazebnik,Pietro Perona,Yoichi Sato,Cordelia Schmid Pdf

The seven-volume set comprising LNCS volumes 7572-7578 constitutes the refereed proceedings of the 12th European Conference on Computer Vision, ECCV 2012, held in Florence, Italy, in October 2012. The 408 revised papers presented were carefully reviewed and selected from 1437 submissions. The papers are organized in topical sections on geometry, 2D and 3D shape, 3D reconstruction, visual recognition and classification, visual features and image matching, visual monitoring: action and activities, models, optimisation, learning, visual tracking and image registration, photometry: lighting and colour, and image segmentation.

Pattern Recognition - Applications and Methods

Author : Pedro Latorre Carmona,J. Salvador Sánchez,Ana L.N. Fred
Publisher : Springer Science & Business Media
Page : 205 pages
File Size : 41,5 Mb
Release : 2013-02-28
Category : Technology & Engineering
ISBN : 9783642365300

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Pattern Recognition - Applications and Methods by Pedro Latorre Carmona,J. Salvador Sánchez,Ana L.N. Fred Pdf

This edited book includes extended and revised versions of a set of selected papers from the First International Conference on Pattern Recognition (ICPRAM 2012), held in Vilamoura, Algarve, Portugal, from 6 to 8 February, 2012, sponsored by the Institute for Systems and Technologies of Information Control and Communication (INSTICC) and held in cooperation with the Association for the Advancement of Artificial Intelligence (AAAI) and Pattern Analysis, Statistical Modelling and Computational Learning (PASCAL2). The conference brought together researchers, engineers and practitioners interested on the areas of Pattern Recognition, both from theoretical and application perspectives.