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Natural Object Recognition
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Book Synopsis Natural Object Recognition by : Thomas M. Strat
Download or read book Natural Object Recognition written by Thomas M. Strat and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Object Recognition presents a totally new approach to the automation of scene understanding. Rather than attempting to construct highly specialized algorithms for recognizing physical objects, as is customary in modern computer vision research, the application and subsequent evaluation of large numbers of relatively straightforward image processing routines is used to recognize natural features such as trees, bushes, and rocks. The use of contextual information is the key to simplifying the problem to the extent that well understood algorithms give reliable results in ground-level, outdoor scenes.
Author :Marco Alexander Treiber Publisher :Springer Science & Business Media ISBN 13 :1849962359 Total Pages :210 pages Book Rating :4.8/5 (499 download)
Book Synopsis An Introduction to Object Recognition by : Marco Alexander Treiber
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.
Book Synopsis Object Recognition in Man, Monkey, and Machine by : Michael J. Tarr
Download or read book Object Recognition in Man, Monkey, and Machine written by Michael J. Tarr and published by MIT Press. This book was released on 1999-03-15 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contributors bring a wide range of methodologies to bear on the common problem of image-based object recognition. These interconnected essays on three-dimensional visual object recognition present cutting-edge research by some of the most creative neuroscientific, cognitive, and computational scientists in the field. Cassandra Moore and Patrick Cavanagh take a classic demonstration, the perception of "two-tone" images, and turn it into a method for understanding the nature of object representations in terms of surfaces and the interaction between bottom-up and top-down processes. Michael J. Tarr and Isabel Gauthier use computer graphics to study whether viewpoint-dependent recognition mechanisms can generalize between exemplars of perceptually defined classes. Melvyn A. Goodale and G. Keith Humphrey use innovative psychophysical techniques to investigate dissociable aspects of visual and spatial processing in brain-injured subjects. D.I. Perrett, M.W. Oram, and E. Ashbridge combine neurophysiological single-cell data from monkeys with computational analyses for a new way of thinking about the mechanisms that mediate viewpoint-dependent object recognition and mental rotation. Shimon Ullman also addresses possible mechanisms to account for viewpoint-dependent behavior, but from the perspective of machine vision. Finally, Philippe G. Schyns synthesizes work from many areas, to provide a coherent account of how stimulus class and recognition task interact. The contributors bring a wide range of methodologies to bear on the common problem of image-based object recognition.
Book Synopsis Object Recognition, Attention, and Action by : Naoyuki Osaka
Download or read book Object Recognition, Attention, and Action written by Naoyuki Osaka and published by Springer Science & Business Media. This book was released on 2009-03-12 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human object recognition is a classical topic both for philosophy and for the natural sciences. Ultimately, understanding of object recognition will be promoted by the cooperation of behavioral research, neurophysiology, and computation. This original book provides an excellent introduction to the issues that are involved. It contains chapters that address the ways in which humans and machines attend to, recognize, and act toward objects in the visual environment.
Book Synopsis High-level Vision by : Shimon Ullman
Download or read book High-level Vision written by Shimon Ullman and published by MIT Press. This book was released on 2000 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: Shimon Ullman focuses on the processes of high-level vision that deal with the interpretation and use of what is seen in the image. In this book, Shimon Ullman focuses on the processes of high-level vision that deal with the interpretation and use of what is seen in the image. In particular, he examines two major problems. The first, object recognition and classification, involves recognizing objects despite large variations in appearance caused by changes in viewing position, illumination, occlusion, and object shape. The second, visual cognition, involves the extraction of shape properties and spatial relations in the course of performing visual tasks such as object manipulation, planning movements in the environment, or interpreting graphical material such as diagrams, graphs and maps. The book first takes up object recognition and develops a novel approach to the recognition of three-dimensional objects. It then studies a number of related issues in high-level vision, including object classification, scene segmentation, and visual cognition. Using computational considerations discussed throughout the book, along with psychophysical and biological data, the final chapter proposes a model for the general flow of information in the visual cortex. Understanding vision is a key problem in the brain sciences, human cognition, and artificial intelligence. Because of the interdisciplinary nature of the theories developed in this work, High-Level Vision will be of interest to readers in all three of these fields.
Book Synopsis Object Recognition by : Tam Phuong Cao
Download or read book Object Recognition written by Tam Phuong Cao and published by BoD – Books on Demand. This book was released on 2011-04-01 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vision-based object recognition tasks are very familiar in our everyday activities, such as driving our car in the correct lane. We do these tasks effortlessly in real-time. In the last decades, with the advancement of computer technology, researchers and application developers are trying to mimic the human's capability of visually recognising. Such capability will allow machine to free human from boring or dangerous jobs.
Book Synopsis Deep Learning for Computer Vision by : Jason Brownlee
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.
Book Synopsis Visual Object Recognition by : Kristen Thielscher
Download or read book Visual Object Recognition written by Kristen Thielscher and published by Springer Nature. This book was released on 2022-05-31 with total page 163 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
Author :Xiaogang Wang Publisher :Foundations and Trends (R) in Signal Processing ISBN 13 :9781680831160 Total Pages :186 pages Book Rating :4.8/5 (311 download)
Book Synopsis Deep Learning in Object Recognition, Detection, and Segmentation by : Xiaogang Wang
Download or read book Deep Learning in Object Recognition, Detection, and Segmentation written by Xiaogang Wang and published by Foundations and Trends (R) in Signal Processing. This book was released on 2016-07-14 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning in Object Recognition, Detection, and Segmentation provides a comprehensive introductory overview of a topic that is having major impact on many areas of research in signal processing, computer vision, and machine learning.
Book Synopsis Advances in Object Recognition Systems by : Ioannis Kypraios
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.
Book Synopsis Representations and Techniques for 3D Object Recognition and Scene Interpretation by : Derek Hoiem
Download or read book Representations and Techniques for 3D Object Recognition and Scene Interpretation written by Derek Hoiem and published by Morgan & Claypool Publishers. This book was released on 2011 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Information Routing, Correspondence Finding, and Object Recognition in the Brain by : Philipp Wolfrum
Download or read book Information Routing, Correspondence Finding, and Object Recognition in the Brain written by Philipp Wolfrum and published by Springer. This book was released on 2010-09-07 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: At?rstsight,thisbookisaboutfacerecognitioninthebrain.Itsmorelasting value, however,lies in the paradigmatic way in which this particular problem is treated. From the basic ideas that are worked out here in concrete detail, it is a naturaland simple next step to at leastimagine, if not realizein model form, much more generalstructures and processes,thus helping to bridge the still tremendous chasm between mind and brain. It is the purpose of this foreword to point out these generic traits. For centuries, thinking about the brain has been dominated by the most complexmechanisticdevicesofthetime,clockwork,communicatinghydraulic tubesor,today,thecomputer.Thecomputer,takenasincarnationoftheU- versal Turing Machine, can implement any conceivable process, so that also a functional brain can surely be simulated on it, an idea that, beginning in the ?fties of the last century, has been seducing scientists to create “art- cial intelligence” in the computer. As a result we now have an information technology that displays many functional capabilities formerly regarded as the exclusive domain of the mind. As fascinating as this is, doting on “int- ligent machines” is systematically diverting our attention awayfrom the true problems of understanding the working of the brain.
Book Synopsis Object Recognition by : M. Bennamoun
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.
Book Synopsis Object Recognition Of Digital Images In Wavelet Neural Network by : Arul Murugan R
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:
Book Synopsis Object Recognition by Computer by : William Eric Leifur Grimson
Download or read book Object Recognition by Computer written by William Eric Leifur Grimson and published by Mit Press. This book was released on 2003-02-01 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes an extended series of experiments into the role of geometry in the critical area of object recognition.
Book Synopsis Computer Vision -- ECCV 2014 by : David Fleet
Download or read book Computer Vision -- ECCV 2014 written by David Fleet and published by Springer. This book was released on 2014-09-22 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 363 revised papers presented were carefully reviewed and selected from 1444 submissions. The papers are organized in topical sections on tracking and activity recognition; recognition; learning and inference; structure from motion and feature matching; computational photography and low-level vision; vision; segmentation and saliency; context and 3D scenes; motion and 3D scene analysis; and poster sessions.
Book Synopsis From Fragments to Objects by : Thomas F. Shipley
Download or read book From Fragments to Objects written by Thomas F. Shipley and published by Elsevier. This book was released on 2001-11-30 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: From Fragments to Objects
