Object Detection And Tracking Using A Parts Based Approach
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Object Detection And Tracking Using A Parts Based Approach
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Author : Daniel S. Clark
language : en
Publisher:
Release Date : 2005
Object Detection And Tracking Using A Parts Based Approach written by Daniel S. Clark and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Automatic tracking categories.
"One of the main goals of artificial intelligence is to allow computers to understand the world around them. As humans we extract a large amount of knowledge about the world from our visual perception, and the field of computer vision is determined to give computers access to this same wealth of knowledge. One of the fundamental steps in understanding the world is finding specific objects within our field of view, and the related task of following these objects as they move. In this thesis the Implicit Shape Model algorithm, a local feature-based object detection algorithm, is implemented and used to develop an appearance model and object tracking algorithm based on it. This algorithm is very robust to intraclass variation, and can successfully track objects when both occlusion and non-stationary backgrounds are present. The usefulness of the proposed appearance model is analyzed, and results of the algorithm on real video sequences are presented. Several enhancements to the method are also proposed, and performance in terms of recall and precision is analyzed"--Abstract.
Moving Object Detection Using Background Subtraction
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Author : Soharab Hossain Shaikh
language : en
Publisher: Springer
Release Date : 2014-06-20
Moving Object Detection Using Background Subtraction written by Soharab Hossain Shaikh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-20 with Computers categories.
This Springer Brief presents a comprehensive survey of the existing methodologies of background subtraction methods. It presents a framework for quantitative performance evaluation of different approaches and summarizes the public databases available for research purposes. This well-known methodology has applications in moving object detection from video captured with a stationery camera, separating foreground and background objects and object classification and recognition. The authors identify common challenges faced by researchers including gradual or sudden illumination change, dynamic backgrounds and shadow and ghost regions. This brief concludes with predictions on the future scope of the methods. Clear and concise, this brief equips readers to determine the most effective background subtraction method for a particular project. It is a useful resource for professionals and researchers working in this field.
Study Of Object Recognition And Identification Based On Shape And Texture Analysis
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Author : Guanqi Wang
language : en
Publisher:
Release Date : 2012
Study Of Object Recognition And Identification Based On Shape And Texture Analysis written by Guanqi Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Object Tracking Technology
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Author : Ashish Kumar
language : en
Publisher: Springer Nature
Release Date : 2023-10-27
Object Tracking Technology written by Ashish Kumar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-27 with Computers categories.
With the increase in urban population, it became necessary to keep track of the object of interest. In favor of SDGs for sustainable smart city, with the advancement in technology visual tracking extends to track multi-target present in the scene rather estimating location for single target only. In contrast to single object tracking, multi-target introduces one extra step of detection. Tracking multi-target includes detecting and categorizing the target into multiple classes in the first frame and provides each individual target an ID to keep its track in the subsequent frames of a video stream. One category of multi-target algorithms exploits global information to track the target of the detected target. On the other hand, some algorithms consider present and past information of the target to provide efficient tracking solutions. Apart from these, deep leaning-based algorithms provide reliable and accurate solutions. But, these algorithms are computationally slow when applied in real-time. This book presents and summarizes the various visual tracking algorithms and challenges in the domain. The various feature that can be extracted from the target and target saliency prediction is also covered. It explores a comprehensive analysis of the evolution from traditional methods to deep learning methods, from single object tracking to multi-target tracking. In addition, the application of visual tracking and the future of visual tracking can also be introduced to provide the future aspects in the domain to the reader. This book also discusses the advancement in the area with critical performance analysis of each proposed algorithm. This book will be formulated with intent to uncover the challenges and possibilities of efficient and effective tracking of single or multi-object, addressing the various environmental and hardware challenges. The intended audience includes academicians, engineers, postgraduate students, developers, professionals, military personals, scientists, data analysts, practitioners, and people who are interested in exploring more about tracking.· Another projected audience are the researchers and academicians who identify and develop methodologies, frameworks, tools, and applications through reference citations, literature reviews, quantitative/qualitative results, and discussions.
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.
Object Recognition
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Author : Tam Phuong Cao
language : en
Publisher: BoD – Books on Demand
Release Date : 2011-04-01
Object Recognition written by Tam Phuong Cao 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 2011-04-01 with Computers categories.
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.
Shape Based Object Detection And Recognition In Silhouettes And Real Images
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Author : Xingwei Yang
language : en
Publisher:
Release Date : 2011
Shape Based Object Detection And Recognition In Silhouettes And Real Images written by Xingwei Yang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computer and Information Science categories.
Computer and Information Science
Deep Learning For Computer Vision
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Author : Jason Brownlee
language : en
Publisher: Machine Learning Mastery
Release Date : 2019-04-04
Deep Learning For Computer Vision written by Jason Brownlee and has been published by Machine Learning Mastery this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-04 with Computers categories.
Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.
Computer Vision Accv 2007
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Author : Yasushi Yagi
language : en
Publisher: Springer
Release Date : 2007-11-14
Computer Vision Accv 2007 written by Yasushi Yagi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-14 with Computers categories.
This title is part of a two volume set that constitutes the refereed proceedings of the 8th Asian Conference on Computer Vision, ACCV 2007. Coverage in this volume includes shape and texture, face and gesture, camera networks, face/gesture/action detection and recognition, learning, motion and tracking, human pose estimation, matching, face/gesture/action detection and recognition, low level vision and phtometory, motion and tracking, human detection, and segmentation.
Recognition By Functional Parts
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Author : Ehud Rivlin
language : en
Publisher:
Release Date : 1994
Recognition By Functional Parts written by Ehud Rivlin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Artificial intelligence categories.
Abstract: "We present an approach to function-based object recognition that reasons about the functionality of an object's intuitive parts. We extend the popular 'recognition by parts' shape recognition framework to support 'recognition by functional parts', by combining a set of functional primitives and their relations with a set of abstract volumetric shape primitives and their relations. Previous approaches have relied on more global object features, often ignoring the problem of object segmentation and thereby restricting themselves to range images of unoccluded scenes. We show how these shape primitives and relations can be easily recovered from superquadric ellipsoids which, in turn, can be recovered from either range or intensity images of occluded scenes. Furthermore, the proposed framework supports both unexpected (bottom-up) object recognition and expected (top-down) object recognition. We demonstrate the approach on a simple domain by recognizing a restricted class of hand-tools from 2-D images."