Shape Based Object Detection and Recognition in Silhouettes and Real Images

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (858 download)

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Book Synopsis Shape Based Object Detection and Recognition in Silhouettes and Real Images by : Xingwei Yang

Download or read book Shape Based Object Detection and Recognition in Silhouettes and Real Images written by Xingwei Yang and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer and Information Science

Practical Machine Learning for Computer Vision

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098102339
Total Pages : 481 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Practical Machine Learning for Computer Vision by : Valliappa Lakshmanan

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

Object Recognition Using Scale-Invariant Chordiogram

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Publisher :
ISBN 13 :
Total Pages : 36 pages
Book Rating : 4.:/5 (13 download)

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Book Synopsis Object Recognition Using Scale-Invariant Chordiogram by : Ashwini Tonge

Download or read book Object Recognition Using Scale-Invariant Chordiogram written by Ashwini Tonge and published by . This book was released on 2017 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis describes an approach for object recognition using the chordiogram shape-based descriptor. Global shape representations are highly susceptible to clutter generated due to the background or other irrelevant objects in real-world images. To overcome the problem, we aim to extract precise object shape using superpixel segmentation, perceptual grouping, and connected components. The employed shape descriptor chordiogram is based on geometric relationships of chords generated from the pairs of boundary points of an object. The chordiogram descriptor applies holistic properties of the shape and also proven suitable for object detection and digit recognition mechanisms. Additionally, it is translation invariant and robust to shape deformations. In spite of such excellent properties, chordiogram is not scale-invariant. To this end, we propose scale invariant chordiogram descriptors and intend to achieve a similar performance before and after applying scale invariance. Our experiments show that we achieve similar performance with and without scale invariance for silhouettes and real world object images. We also show experiments at different scales to confirm that we obtain scale invariance for chordiogram.

Computer Vision And Shape Recognition

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Publisher : World Scientific
ISBN 13 : 9814525138
Total Pages : 463 pages
Book Rating : 4.8/5 (145 download)

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Book Synopsis Computer Vision And Shape Recognition by : Ching Yee Suen

Download or read book Computer Vision And Shape Recognition written by Ching Yee Suen and published by World Scientific. This book was released on 1989-04-01 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an up-to-date volume of selected and expanded papers originating from Vision Interface 88, a conference held in Edmonton, Canada. A broad range of topics are covered-from image processing to hardware design. They include robot vision, biomedical imaging, remote sensing and parallel processing, shape recognition and features, computational methods in vision, and three dimensional vision and application.

Object Detection and Recognition in Digital Images

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Publisher : Wiley
ISBN 13 : 9780470976371
Total Pages : 548 pages
Book Rating : 4.9/5 (763 download)

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Book Synopsis Object Detection and Recognition in Digital Images by : Boguslaw Cyganek

Download or read book Object Detection and Recognition in Digital Images written by Boguslaw Cyganek and published by Wiley. This book was released on 2013-08-05 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Visual Object Recognition

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Publisher : Morgan & Claypool Publishers
ISBN 13 : 1598299689
Total Pages : 184 pages
Book Rating : 4.5/5 (982 download)

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Book Synopsis Visual Object Recognition by : Kristen Grauman

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

Image and Signal Processing

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Publisher : Springer
ISBN 13 : 3642312543
Total Pages : 607 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Image and Signal Processing by : Abderrahim Elmoataz

Download or read book Image and Signal Processing written by Abderrahim Elmoataz and published by Springer. This book was released on 2012-07-04 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th International Conference on Image and Signal Processing, ICISP 2012, held in Agadir, Morocco, in June 2012. The 75 revised full papers presented were carefully reviewed and selected from 158 submissions. The contributions are grouped into the following topical sections: multi/hyperspectral imaging; image itering and coding; signal processing; biometric; watermarking and texture; segmentation and retieval; image processing; pattern recognition.

Computer Vision - ECCV 2004

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Publisher : Springer Science & Business Media
ISBN 13 : 354021982X
Total Pages : 639 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Computer Vision - ECCV 2004 by : Tomas Pajdla

Download or read book Computer Vision - ECCV 2004 written by Tomas Pajdla and published by Springer Science & Business Media. This book was released on 2004-04-30 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: The four-volume set comprising LNCS volumes 3021/3022/3023/3024 constitutes the refereed proceedings of the 8th European Conference on Computer Vision, ECCV 2004, held in Prague, Czech Republic, in May 2004. The 190 revised papers presented were carefully reviewed and selected from a total of 555 papers submitted. The four books span the entire range of current issues in computer vision. The papers are organized in topical sections on tracking; feature-based object detection and recognition; geometry; texture; learning and recognition; information-based image processing; scale space, flow, and restoration; 2D shape detection and recognition; and 3D shape representation and reconstruction.

Communication, Cloud and Big Data

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Publisher : ACCB Publishing
ISBN 13 : 1908368039
Total Pages : 167 pages
Book Rating : 4.9/5 (83 download)

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Book Synopsis Communication, Cloud and Big Data by : Hiren Kumar Deva Sarma

Download or read book Communication, Cloud and Big Data written by Hiren Kumar Deva Sarma and published by ACCB Publishing. This book was released on 2014-12-31 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analysis of big data is becoming a hot stuff for engineers, researchers and business enterprises now a days. It refers to the process of collecting, organizing and analyzing large sets of data to discover hidden patterns and other useful information. Not solely can massive information analytics assist to know the knowledge contained inside the information, however it will additionally facilitate to determine the information that is most significant to the business and future business choices. Cloud computing is the type of computing that relies on sharing computing resources rather than having local servers or personal devices to handle applications. Cloud computing aims at applying traditional supercomputing, or high-performance computing power to perform tens of trillions of computations per second, in consumer-oriented applications such as financial portfolios, to deliver personalized information, to provide data storage etc. Since big data places on networks, storage and servers, requirements arise to analyse this huge amount data on the cloud. Even cloud providers also welcome this new business opportunity of supporting big data analysis in the cloud. But in the same time they are facing various, architectural and technical hurdles. Therefore, big data analysis in cloud attacting many researchers now a days. The National Conference on Communication, Cloud and Big Data (CCB) 2014 organized by Department of Information Technology, SMIT has received keen response from researchers across the country. Each paper went through reviews process and finally, 30 papers were selected for presentation. The papers are an even mix of research topics from the fields of Communication, Cloud and Big Data and its applications in various fields of engineering and science.

Study of Object Recognition and Identification Based on Shape and Texture Analysis

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (862 download)

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Book Synopsis Study of Object Recognition and Identification Based on Shape and Texture Analysis by : Guanqi Wang

Download or read book Study of Object Recognition and Identification Based on Shape and Texture Analysis written by Guanqi Wang and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Object Detection and Recognition in Digital Images

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Publisher : John Wiley & Sons
ISBN 13 : 111861836X
Total Pages : 518 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Object Detection and Recognition in Digital Images by : Boguslaw Cyganek

Download or read book Object Detection and Recognition in Digital Images written by Boguslaw Cyganek and published by John Wiley & Sons. This book was released on 2013-05-20 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Representations and Techniques for 3D Object Recognition and Scene Interpretation

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Publisher : Morgan & Claypool Publishers
ISBN 13 : 1608457281
Total Pages : 172 pages
Book Rating : 4.6/5 (84 download)

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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

Object Recognition by Computer

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Publisher : Mit Press
ISBN 13 : 9780262571883
Total Pages : 532 pages
Book Rating : 4.5/5 (718 download)

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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.

Hierarchical Approach for Object Detection Using Shape Descriptors

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Publisher : LAP Lambert Academic Publishing
ISBN 13 : 9783330353060
Total Pages : 56 pages
Book Rating : 4.3/5 (53 download)

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Book Synopsis Hierarchical Approach for Object Detection Using Shape Descriptors by : Bassam Syed Arshad

Download or read book Hierarchical Approach for Object Detection Using Shape Descriptors written by Bassam Syed Arshad and published by LAP Lambert Academic Publishing. This book was released on 2019-05-28 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic object recognition is a fundamental problem in the fields of computer vision and machine learning, that has received a lot of research attention lately. While there are different methods, that build upon various low level features to construct object models, this work explores and implements the use of closed-contours as formidable object features. A hierarchical technique is employed to extract the contours, exploiting the inherent spatial relationships between the parent and child contours of an object. Fourier Descriptors are used to effectively and invariantly describe the extracted contours. A simple hierarchical, shape label and spatial descriptor matching method is implemented, to determine the nearest object-model. Multi-threaded architecture and GPU efficient image-processing functions are adopted making the technique efficient for use in real world applications. The technique is successfully tested on common traffic signs in real world images, with overall good performance and robustness being obtained as an end result.

Guiding Object Recognition

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Publisher :
ISBN 13 :
Total Pages : 162 pages
Book Rating : 4.:/5 (618 download)

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Book Synopsis Guiding Object Recognition by : Timothy M. Lebo

Download or read book Guiding Object Recognition written by Timothy M. Lebo and published by . This book was released on 2005 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis presents a components-based object detection and localization algorithm for static images as well as a detailed analysis of the model dynamics during the localization process.

Shape Perception in Human and Computer Vision

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Publisher : Springer Science & Business Media
ISBN 13 : 144715195X
Total Pages : 505 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Shape Perception in Human and Computer Vision by : Sven J. Dickinson

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.

From Shape-based Object Recognition and Discovery to 3D Scene Interpretation

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Publisher :
ISBN 13 :
Total Pages : 130 pages
Book Rating : 4.:/5 (723 download)

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Book Synopsis From Shape-based Object Recognition and Discovery to 3D Scene Interpretation by : Nadia Payet

Download or read book From Shape-based Object Recognition and Discovery to 3D Scene Interpretation written by Nadia Payet and published by . This book was released on 2011 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation addresses a number of inter-related and fundamental problems in computer vision. Specifically, we address object discovery, recognition, segmentation, and 3D pose estimation in images, as well as 3D scene reconstruction and scene interpretation. The key ideas behind our approaches include using shape as a basic object feature, and using structured prediction modeling paradigms for representing objects and scenes. In this work, we make a number of new contributions both in computer vision and machine learning. We address the vision problems of shape matching, shape-based mining of objects in arbitrary image collections, context-aware object recognition, monocular estimation of 3D object poses, and monocular 3D scene reconstruction using shape from texture. Our work on shape-based object discovery is the first to show that meaningful objects can be extracted from a collection of arbitrary images, without any human supervision, by shape matching. We also show that a spatial repetition of objects in images (e.g., windows on a building facade, or cars lined up along a street) can be used for 3D scene reconstruction from a single image. The aforementioned topics have never been addressed in the literature. The dissertation also presents new algorithms and object representations for the aforementioned vision problems. We fuse two traditionally different modeling paradigms Conditional Random Fields (CRF) and Random Forests (RF) into a unified framework, referred to as (RF)^2. We also derive theoretical error bounds of estimating distribution ratios by a two-class RF, which is then used to derive the theoretical performance bounds of a two-class (RF)^2. Thorough experimental evaluation of individual aspects of all our approaches is presented. In general, the experiments demonstrate that we outperform the state of the art on the benchmark datasets, without increasing complexity and supervision in training.