Object Categorization
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Author | : Sven J. Dickinson |
Publisher | : Cambridge University Press |
Total Pages | : 553 |
Release | : 2009-09-07 |
Genre | : Computers |
ISBN | : 0521887380 |
A unique multidisciplinary perspective on the problem of visual object categorization.
Author | : Axel Pinz |
Publisher | : Now Publishers Inc |
Total Pages | : 110 |
Release | : 2006 |
Genre | : Computers |
ISBN | : 1933019131 |
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.
Author | : Henri Cohen |
Publisher | : Elsevier |
Total Pages | : 1277 |
Release | : 2017-06-03 |
Genre | : Psychology |
ISBN | : 0128097663 |
Handbook of Categorization in Cognitive Science, Second Edition presents the study of categories and the process of categorization as viewed through the lens of the founding disciplines of the cognitive sciences, and how the study of categorization has long been at the core of each of these disciplines. The literature on categorization reveals there is a plethora of definitions, theories, models and methods to apprehend this central object of study. The contributions in this handbook reflect this diversity. For example, the notion of category is not uniform across these contributions, and there are multiple definitions of the notion of concept. Furthermore, the study of category and categorization is approached differently within each discipline. For some authors, the categories themselves constitute the object of study, whereas for others, it is the process of categorization, and for others still, it is the technical manipulation of large chunks of information. Finally, yet another contrast has to do with the biological versus artificial nature of agents or categorizers. - Defines notions of category and categorization - Discusses the nature of categories: discrete, vague, or other - Explores the modality effects on categories - Bridges the category divide - calling attention to the bridges that have already been built, and avenues for further cross-fertilization between disciplines
Author | : Pekka Harni |
Publisher | : |
Total Pages | : 122 |
Release | : 2010 |
Genre | : Categorization (Linguistics) |
ISBN | : 9789526000299 |
Finnish architect Pekka Harni runs a design and architecture practice in Helsinki together with industrial designer Yuka Takahashi. Their collaboration results in a variety of work, of which this book on the classification of objects is just one part. Based on a morphological-functional consideration of the properties of household objects, the study proposes to organise the forms of artefacts, determine the significance of their parts and explain the relationships between objects and the environment, thus describing their most important basic properties while exploring the realm of functional form.
Author | : Lisa Gershkoff-Stowe |
Publisher | : Psychology Press |
Total Pages | : 482 |
Release | : 2005-05-06 |
Genre | : Psychology |
ISBN | : 1135626243 |
This book covers a broad range of current research topics in category development. Its aim is to understand the perceptual and cognitive mechanisms that underlie category formation and how they change in developmental time. The chapters in this book are
Author | : Jean Ponce |
Publisher | : Springer |
Total Pages | : 622 |
Release | : 2007-01-25 |
Genre | : Computers |
ISBN | : 3540687955 |
This volume is a post-event proceedings volume and contains selected papers based on presentations given, and vivid discussions held, during two workshops held in Taormina in 2003 and 2004. The 30 thoroughly revised papers presented are organized in the following topical sections: recognition of specific objects, recognition of object categories, recognition of object categories with geometric relations, and joint recognition and segmentation.
Author | : Chris Fields |
Publisher | : Frontiers Media SA |
Total Pages | : 267 |
Release | : 2016-08-18 |
Genre | : Psychology |
ISBN | : 2889199401 |
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.
Author | : Joaquim Filipe |
Publisher | : Springer Science & Business Media |
Total Pages | : 1002 |
Release | : 2009-05-04 |
Genre | : Business & Economics |
ISBN | : 3642013473 |
This book contains the collection of full papers accepted at the 11th International Conference on Enterprise Information Systems (ICEIS 2009), organized by the Ins- tute for Systems and Technologies of Information Control and Communication (INSTICC) in cooperation with the Association for Advancement of Artificial Intel- gence (AAAI) and ACM SIGMIS (SIG on Management Information Systems), and technically co-sponsored by the Japanese IEICE SWIM (SIG on Software Interprise Modeling) and the Workflow Management Coalition (WfMC). ICEIS 2009 was held in Milan, Italy. This conference has grown to become a - jor point of contact between research scientists, engineers and practitioners in the area of business applications of information systems. This year, five simultaneous tracks were held, covering different aspects related to enterprise computing, including: “- tabases and Information Systems Integration,” “Artificial Intelligence and Decision Support Systems,” “Information Systems Analysis and Specification,” “Software Agents and Internet Computing” and “Human–Computer Interaction”. All tracks describe research work that is often oriented toward real-world applications and hi- light the benefits of information systems and technology for industry and services, thus making a bridge between academia and enterprise. ICEIS 2009 received 644 paper submissions from 70 countries in all continents; 81 papers were published and presented as full papers, i.e., completed research work (8 pages/30-minute oral presentation). Additional papers accepted at ICEIS, including short papers and posters, were published in the regular conference proceedings.
Author | : James Kwok |
Publisher | : Springer Science & Business Media |
Total Pages | : 670 |
Release | : 2010-05-20 |
Genre | : Computers |
ISBN | : 3642133177 |
This book and its sister volume constitute the proceedings of the 7th International Symposium on Neural Networks, ISNN 2010, held in Shanghai, China, June 6-9, 2010. The 170 revised full papers of Part I and Part II were carefully selected from 591 submissions and focus on topics such as SVM and Kernel Methods, Vision and Image, Data Mining and Text Analysis, BCI and Brain Imaging and its applications. The first volume, Part I (LNCS 6063) covers the following topics: Neuropysiological Foundation, Theory and Models, Learning and Inference, and Nerodynamics.
Author | : Derek Santhanam |
Publisher | : Springer Nature |
Total Pages | : 147 |
Release | : 2022-05-31 |
Genre | : Computers |
ISBN | : 3031015576 |
One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physical scenes from images. The second section introduces representations for 3D object categories that account for the intrinsically 3D nature of objects and provide robustness to change in viewpoints. The third section discusses strategies to unite inference of scene geometry and object pose and identity into a coherent scene interpretation. Each section broadly surveys important ideas from cognitive science and artificial intelligence research, organizes and discusses key concepts and techniques from recent work in computer vision, and describes a few sample approaches in detail. Newcomers to computer vision will benefit from introductions to basic concepts, such as single-view geometry and image classification, while experts and novices alike may find inspiration from the book's organization and discussion of the most recent ideas in 3D scene understanding and 3D object recognition. Specific topics include: mathematics of perspective geometry; visual elements of the physical scene, structural 3D scene representations; techniques and features for image and region categorization; historical perspective, computational models, and datasets and machine learning techniques for 3D object recognition; inferences of geometrical attributes of objects, such as size and pose; and probabilistic and feature-passing approaches for contextual reasoning about 3D objects and scenes. Table of Contents: Background on 3D Scene Models / Single-view Geometry / Modeling the Physical Scene / Categorizing Images and Regions / Examples of 3D Scene Interpretation / Background on 3D Recognition / Modeling 3D Objects / Recognizing and Understanding 3D Objects / Examples of 2D 1/2 Layout Models / Reasoning about Objects and Scenes / Cascades of Classifiers / Conclusion and Future Directions