2d Object Detection And Recognition


2d Object Detection And Recognition
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2d Object Detection And Recognition


2d Object Detection And Recognition
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Author : Yali Amit
language : en
Publisher: MIT Press
Release Date : 2002

2d Object Detection And Recognition written by Yali Amit and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.


A guide to the computer detection and recognition of 2D objects in gray-level images.



Representations And Techniques For 3d Object Recognition And Scene Interpretation


Representations And Techniques For 3d Object Recognition And Scene Interpretation
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Author : Derek Hoiem
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2011-09-09

Representations And Techniques For 3d Object Recognition And Scene Interpretation written by Derek Hoiem and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-09 with Technology & Engineering categories.


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



Object Detection And Recognition In Digital Images


Object Detection And Recognition In Digital Images
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Author : Boguslaw Cyganek
language : en
Publisher: John Wiley & Sons
Release Date : 2013-05-20

Object Detection And Recognition In Digital Images written by Boguslaw Cyganek and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-20 with Science categories.


Object detection, tracking and recognition in images are key problems in computer vision. This book provides the reader with a balanced treatment between the theory and practice of selected methods in these areas to make the book accessible to a range of researchers, engineers, developers and postgraduate students working in computer vision and related fields. Key features: Explains the main theoretical ideas behind each method (which are augmented with a rigorous mathematical derivation of the formulas), their implementation (in C++) and demonstrated working in real applications. Places an emphasis on tensor and statistical based approaches within object detection and recognition. Provides an overview of image clustering and classification methods which includes subspace and kernel based processing, mean shift and Kalman filter, neural networks, and k-means methods. Contains numerous case study examples of mainly automotive applications. Includes a companion website hosting full C++ implementation, of topics presented in the book as a software library, and an accompanying manual to the software platform.



Deep Learning In Object Detection And Recognition


Deep Learning In Object Detection And Recognition
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Author : Xiaoyue Jiang
language : en
Publisher: Springer
Release Date : 2018-09-11

Deep Learning In Object Detection And Recognition written by Xiaoyue Jiang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-11 with Computers categories.


This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks.



Toward Category Level Object Recognition


Toward Category Level Object Recognition
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Author : Jean Ponce
language : en
Publisher: Springer
Release Date : 2007-01-25

Toward Category Level Object Recognition written by Jean Ponce and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-01-25 with Computers categories.


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.



Visual Object Recognition


Visual Object Recognition
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Author : Kristen Grauman
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2011

Visual Object Recognition written by Kristen Grauman and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computers categories.


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



Object Detection By Stereo Vision Images


Object Detection By Stereo Vision Images
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Author : R. Arokia Priya
language : en
Publisher: John Wiley & Sons
Release Date : 2022-09-14

Object Detection By Stereo Vision Images written by R. Arokia Priya and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-14 with Computers categories.


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.



Deep Learning In Object Detection And Recognition


Deep Learning In Object Detection And Recognition
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Author : Xiaoyue Jiang
language : en
Publisher: Springer
Release Date : 2020-11-27

Deep Learning In Object Detection And Recognition written by Xiaoyue Jiang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-27 with Computers categories.


This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks.



Human Ear Recognition By Computer


Human Ear Recognition By Computer
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Author : Bir Bhanu
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-02-26

Human Ear Recognition By Computer written by Bir Bhanu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-26 with Computers categories.


At the frontier of research, this book offers complete coverage of human ear recognition. It explores all aspects of 3D ear recognition: representation, detection, recognition, indexing and performance prediction. It uses large datasets to quantify and compare the performance of various techniques. Features and topics include: Ear detection and recognition in 2D image; 3D object recognition and 3D biometrics; 3D ear recognition; Performance comparison and prediction.



Visual Object Tracking With Deep Neural Networks


Visual Object Tracking With Deep Neural Networks
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Author : Pier Luigi Mazzeo
language : en
Publisher: BoD – Books on Demand
Release Date : 2019-12-18

Visual Object Tracking With Deep Neural Networks written by Pier Luigi Mazzeo and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-18 with Computers categories.


Visual object tracking (VOT) and face recognition (FR) are essential tasks in computer vision with various real-world applications including human-computer interaction, autonomous vehicles, robotics, motion-based recognition, video indexing, surveillance and security. This book presents the state-of-the-art and new algorithms, methods, and systems of these research fields by using deep learning. It is organized into nine chapters across three sections. Section I discusses object detection and tracking ideas and algorithms; Section II examines applications based on re-identification challenges; and Section III presents applications based on FR research.