Background Modeling and Foreground Detection for Video Surveillance

Background Modeling and Foreground Detection for Video Surveillance PDF Author: Thierry Bouwmans
Publisher: CRC Press
ISBN: 1482205386
Category : Computers
Languages : en
Pages : 633

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Book Description
Background modeling and foreground detection are important steps in video processing used to detect robustly moving objects in challenging environments. This requires effective methods for dealing with dynamic backgrounds and illumination changes as well as algorithms that must meet real-time and low memory requirements.Incorporating both establish

Background Modeling and Foreground Detection for Video Surveillance

Background Modeling and Foreground Detection for Video Surveillance PDF Author: Thierry Bouwmans
Publisher: CRC Press
ISBN: 1482205386
Category : Computers
Languages : en
Pages : 633

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Book Description
Background modeling and foreground detection are important steps in video processing used to detect robustly moving objects in challenging environments. This requires effective methods for dealing with dynamic backgrounds and illumination changes as well as algorithms that must meet real-time and low memory requirements.Incorporating both establish

Background Modeling and Foreground Detection for Video Surveillance

Background Modeling and Foreground Detection for Video Surveillance PDF Author: Thierry Bouwmans
Publisher: CRC Press
ISBN: 1482205378
Category : Computers
Languages : en
Pages : 634

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Book Description
Background modeling and foreground detection are important steps in video processing used to detect robustly moving objects in challenging environments. This requires effective methods for dealing with dynamic backgrounds and illumination changes as well as algorithms that must meet real-time and low memory requirements. Incorporating both established and new ideas, Background Modeling and Foreground Detection for Video Surveillance provides a complete overview of the concepts, algorithms, and applications related to background modeling and foreground detection. Leaders in the field address a wide range of challenges, including camera jitter and background subtraction. The book presents the top methods and algorithms for detecting moving objects in video surveillance. It covers statistical models, clustering models, neural networks, and fuzzy models. It also addresses sensors, hardware, and implementation issues and discusses the resources and datasets required for evaluating and comparing background subtraction algorithms. The datasets and codes used in the text, along with links to software demonstrations, are available on the book’s website. A one-stop resource on up-to-date models, algorithms, implementations, and benchmarking techniques, this book helps researchers and industry developers understand how to apply background models and foreground detection methods to video surveillance and related areas, such as optical motion capture, multimedia applications, teleconferencing, video editing, and human–computer interfaces. It can also be used in graduate courses on computer vision, image processing, real-time architecture, machine learning, or data mining.

Handbook Of Pattern Recognition And Computer Vision (2nd Edition)

Handbook Of Pattern Recognition And Computer Vision (2nd Edition) PDF Author: Chi Hau Chen
Publisher: World Scientific
ISBN: 9814497649
Category : Computers
Languages : en
Pages : 1045

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Book Description
The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.

Moving Object Detection Using Background Subtraction

Moving Object Detection Using Background Subtraction PDF Author: Soharab Hossain Shaikh
Publisher: Springer
ISBN: 3319073869
Category : Computers
Languages : en
Pages : 74

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Book Description
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.

Computer Vision -- ACCV 2012

Computer Vision -- ACCV 2012 PDF Author: Kyoung Mu Lee
Publisher: Springer
ISBN: 364237431X
Category : Computers
Languages : en
Pages : 764

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Book Description
The four-volume set LNCS 7724--7727 constitutes the thoroughly refereed post-conference proceedings of the 11th Asian Conference on Computer Vision, ACCV 2012, held in Daejeon, Korea, in November 2012. The total of 226 contributions presented in these volumes was carefully reviewed and selected from 869 submissions. The papers are organized in topical sections on object detection, learning and matching; object recognition; feature, representation, and recognition; segmentation, grouping, and classification; image representation; image and video retrieval and medical image analysis; face and gesture analysis and recognition; optical flow and tracking; motion, tracking, and computational photography; video analysis and action recognition; shape reconstruction and optimization; shape from X and photometry; applications of computer vision; low-level vision and applications of computer vision.

Video Surveillance for Sensor Platforms

Video Surveillance for Sensor Platforms PDF Author: Mayssaa Al Najjar
Publisher: Springer Science & Business Media
ISBN: 1461418577
Category : Technology & Engineering
Languages : en
Pages : 215

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Book Description
This book introduces resource aware image decomposition, registration, fusion, object detection and tracking algorithms along with their applications in security, monitoring and integration in 3rd Generation Surveillance Systems. All algorithms are evaluated through experimental and simulation results and a parallel and pipelined efficient architecture for implementing the algorithms is described.

From Visual Surveillance to Internet of Things

From Visual Surveillance to Internet of Things PDF Author: Lavanya Sharma
Publisher: CRC Press
ISBN: 1000708101
Category : Computers
Languages : en
Pages : 277

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Book Description
From Visual Surveillance to Internet of Things: Technology and Applications is an invaluable resource for students, academicians and researchers to explore the utilization of Internet of Things with visual surveillance and its underlying technologies in different application areas. Using a series of present and future applications – business insights, indoor-outdoor securities, smart grids, human detection and tracking, intelligent traffic monitoring, e-health department and many more – this book will support readers to obtain a deeper knowledge in implementing IoT with visual surveillance. The book offers comprehensive coverage of the most essential topics, including: The rise of machines and communications to IoT (3G, 5G) Tools and technologies of IoT with visual surveillance IoT with visual surveillance for real-time applications IoT architectures Challenging issues and novel solutions for realistic applications Mining and tracking of motion-based object data Image processing and analysis into the unified framework to understand both IOT and computer vision applications This book will be an ideal resource for IT professionals, researchers, under- or post-graduate students, practitioners, and technology developers who are interested in gaining a deeper knowledge in implementing IoT with visual surveillance, critical applications domains, technologies, and solutions to handle relevant challenges. Dr. Lavanya Sharma is an Assistant Professor in the Amity Institute of Information Technology at Amity University UP, Noida, India. She is a recipient of several prestigious awards during her academic career. She is an active nationally-recognized researcher who has published numerous papers in her field. She has contributed as an Organizing Committee member and session chair at Springer and IEEE conferences. Prof. Pradeep K. Garg worked as a Vice Chancellor, Uttarakhand Technical University, Dehradun. Presently he is working in the department of Civil Engineering, IIT Roorkee as a professor. Prof. Garg has published more than 300 technical papers in national and international conferences and journals. He has completed 26 research projects funded by various government agencies, guided 27 PhD candidates, and provided technical services to 84 consultancy projects on various aspects of Civil Engineering.

Handbook on Soft Computing for Video Surveillance

Handbook on Soft Computing for Video Surveillance PDF Author: Sankar K. Pal
Publisher: CRC Press
ISBN: 1439856842
Category : Mathematics
Languages : en
Pages : 344

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Book Description
Information on integrating soft computing techniques into video surveillance is widely scattered among conference papers, journal articles, and books. Bringing this research together in one source, Handbook on Soft Computing for Video Surveillance illustrates the application of soft computing techniques to different tasks in video surveillance. Worldwide experts in the field present novel solutions to video surveillance problems and discuss future trends. After an introduction to video surveillance systems and soft computing tools, the book gives examples of neural network-based approaches for solving video surveillance tasks and describes summarization techniques for content identification. Covering a broad spectrum of video surveillance topics, the remaining chapters explain how soft computing techniques are used to detect moving objects, track objects, and classify and recognize target objects. The book also explores advanced surveillance systems under development. Incorporating both existing and new ideas, this handbook unifies the basic concepts, theories, algorithms, and applications of soft computing. It demonstrates why and how soft computing methodologies can be used in various video surveillance problems.

Moving Object Detection Using Background Subtraction Algorithms

Moving Object Detection Using Background Subtraction Algorithms PDF Author: Priyank Shah
Publisher: GRIN Verlag
ISBN: 3656672660
Category : Computers
Languages : en
Pages : 64

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Book Description
Master's Thesis from the year 2014 in the subject Computer Science - Theory, grade: 9.2, , language: English, abstract: In this thesis we present an operational computer video system for moving object detection and tracking . The system captures monocular frames of background as well as moving object and to detect tracking and identifies those moving objects. An approach to statistically modeling of moving object developed using Background Subtraction Algorithms. There are many methods proposed for Background Subtraction algorithm in past years. Background subtraction algorithm is widely used for real time moving object detection in video surveillance system. In this paper we have studied and implemented different types of methods used for segmentation in Background subtraction algorithm with static camera. This paper gives good understanding about procedure to obtain foreground using existing common methods of Background Subtraction, their complexity, utility and also provide basics which will useful to improve performance in the future . First, we have explained the basic steps and procedure used in vision based moving object detection. Then, we have debriefed the common methods of background subtraction like Simple method, statistical methods like Mean and Median filter, Frame Differencing and W4 System method , Running Gaussian Average and Gaussian Mixture Model and last is Eigenbackground Model. After that we have implemented all the above techniques on MATLAB software and show some experimental results for the same and compare them in terms of speed and complexity criteria. Also we have improved one of the GMM algorithm by combining it with optical flow method, which is also good method to detect moving elements.

Computer Vision and Internet of Things

Computer Vision and Internet of Things PDF Author: Lavanya Sharma
Publisher: CRC Press
ISBN: 100057055X
Category : Computers
Languages : en
Pages : 319

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Book Description
Computer Vision and Internet of Things: Technologies and Applications explores the utilization of Internet of Things (IoT) with computer vision and its underlying technologies in different applications areas. Using a series of present and future applications – including business insights, indoor-outdoor securities, smart grids, human detection and tracking, intelligent traffic monitoring, e-health departments, and medical imaging – this book focuses on providing a detailed description of the utilization of IoT with computer vision and its underlying technologies in critical application areas, such as smart grids, emergency departments, intelligent traffic cams, insurance, and the automotive industry. Key Features • Covers the challenging issues related to sensors, detection, and tracking of moving objects with solutions to handle relevant challenges • Describes the latest technological advances in IoT and computer vision with their implementations • Combines image processing and analysis into a unified framework to understand both IOT and computer vision applications • Explores mining and tracking of motion-based object data, such as trajectory prediction and prediction of a particular location of object data, and their critical applications • Provides novel solutions for medical imaging (skin lesion detection, cancer detection, enhancement techniques for MRI images, and automated disease prediction) This book is primarily aimed at graduates and researchers working in the areas of IoT, computer vision, big data, cloud computing, and remote sensing. It is also an ideal resource for IT professionals and technology developers.