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Multi Camera Networks

Multi Camera Networks Book
Author : Hamid Aghajan,Andrea Cavallaro
Publisher : Academic Press
Release : 2009-04-25
ISBN : 9780080878003
Language : En, Es, Fr & De

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Book Description :

The first book, by the leading experts, on this rapidly developing field with applications to security, smart homes, multimedia, and environmental monitoring Comprehensive coverage of fundamentals, algorithms, design methodologies, system implementation issues, architectures, and applications Presents in detail the latest developments in multi-camera calibration, active and heterogeneous camera networks, multi-camera object and event detection, tracking, coding, smart camera architecture and middleware This book is the definitive reference in multi-camera networks. It gives clear guidance on the conceptual and implementation issues involved in the design and operation of multi-camera networks, as well as presenting the state-of-the-art in hardware, algorithms and system development. The book is broad in scope, covering smart camera architectures, embedded processing, sensor fusion and middleware, calibration and topology, network-based detection and tracking, and applications in distributed and collaborative methods in camera networks. This book will be an ideal reference for university researchers, R&D engineers, computer engineers, and graduate students working in signal and video processing, computer vision, and sensor networks. Hamid Aghajan is a Professor of Electrical Engineering (consulting) at Stanford University. His research is on multi-camera networks for smart environments with application to smart homes, assisted living and well being, meeting rooms, and avatar-based communication and social interactions. He is Editor-in-Chief of Journal of Ambient Intelligence and Smart Environments, and was general chair of ACM/IEEE ICDSC 2008. Andrea Cavallaro is Reader (Associate Professor) at Queen Mary, University of London (QMUL). His research is on target tracking and audiovisual content analysis for advanced surveillance and multi-sensor systems. He serves as Associate Editor of the IEEE Signal Processing Magazine and the IEEE Trans. on Multimedia, and has been general chair of IEEE AVSS 2007, ACM/IEEE ICDSC 2009 and BMVC 2009. The first book, by the leading experts, on this rapidly developing field with applications to security, smart homes, multimedia, and environmental monitoring Comprehensive coverage of fundamentals, algorithms, design methodologies, system implementation issues, architectures, and applications Presents in detail the latest developments in multi-camera calibration, active and heterogeneous camera networks, multi-camera object and event detection, tracking, coding, smart camera architecture and middleware

Design and Performance of Multi camera Networks

Design and Performance of Multi camera Networks Book
Author : Itai Katz
Publisher : Unknown
Release : 2010
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Camera networks have recently been proposed as a sensor modality for 3D localization and tracking tasks. Recent advances in computer vision and decreasing equipment costs have made the use of video cameras increasingly favorable. Their extensibility, unobtrusiveness, and low cost make camera networks an appealing sensor for a broad range of applications. However, due to the complex interaction between system parameters and their impact on performance, designing these systems is currently as much an art as a science. Specifically, the designer must minimize the error (where the error function may be unique to each application) by varying the camera network's configuration, all while obeying constraints imposed by scene geometry, budget, and minimum required work volume. Designers often have no objective sense of how the main parameters drive performance, resulting in a configuration based primarily on intuition. Without an objective process to search through the enormous parameter space, camera networks have enjoyed moderate success as a laboratory tool but have yet to realize their commercial potential. In this thesis we develop a systematic methodology to improve the design of multi-camera networks. First, we explore the impact of varying system parameters on performance motivated by a 3D localization task. The parameters we investigate include those pertaining to the camera (resolution, field of view, etc.), the environment (work volume and degree of occlusion) and noise sources. Ultimately, we seek to provide insights to common questions facing camera network designers: How many cameras are needed? Of what type? How should they be placed? First, to help designers efficiently explore the vast parameter spaces inherent in multi-camera network design, we develop a camera network simulation environment to rapidly evaluate potential configurations. Using this simulation, we propose a new method for camera network configuration based on genetic algorithms. Starting from an initially random population of configurations, we demonstrate how an optimal camera network configuration can be evolved, without a priori knowledge of the interdependencies between parameters. This numerical approach is adaptable to different environments or application requirements and can efficiently accommodate a high-dimensional search space, while producing superior results to hand-designed camera networks. The proposed method is both easier to implement than a hand-designed network and is more accurate, as measured by 3D point reconstruction error. Next, with the fundamentals of multi-camera network design in place, we then demonstrate how the system can be applied to a common computer vision task, namely, 3D localization and tracking. The typical approach to localization and tracking is to apply traditional 2D algorithms (that is, those designed to operate on the image plane) to multiple cameras and fuse the results. We describe a new method which takes the noise sources inherent to camera networks into account. By modeling the velocity of the tracked object in addition to position we can compensate for synchronization errors between cameras in the network, thereby reducing the localization error. Through this experiment we provide evidence that algorithms specific to multi-camera networks perform better than straightforward extensions of their single-camera counterparts. Finally, we verify the efficacy of the camera network configuration and 3D tracking algorithms by demonstrating their use in empirical experiments. The results obtained were similar to the results produced by the simulated environment.

Multi camera Networks Principles and Applications

Multi camera Networks  Principles and Applications Book
Author : Druin
Publisher : Unknown
Release : 2009
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

This book is the definitive reference in multi-camera networks. It gives clear guidance on the conceptual and implementation issues involved in the design and operation of multi-camera networks, as well as presenting the state-of-the-art in hardware, algo.

Camera Networks

Camera Networks Book
Author : Amit Roy-Chodhury,Bi Song
Publisher : Morgan & Claypool Publishers
Release : 2012-01-01
ISBN : 1608456757
Language : En, Es, Fr & De

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Book Description :

As networks of video cameras are installed in many applications like security and surveillance, environmental monitoring, disaster response, and assisted living facilities, among others, image understanding in camera networks is becoming an important area of research and technology development. There are many challenges that need to be addressed in the process. Some of them are listed below: - Traditional computer vision challenges in tracking and recognition, robustness to pose, illumination, occlusion, clutter, recognition of objects, and activities; - Aggregating local information for wide area scene understanding, like obtaining stable, long-term tracks of objects; - Positioning of the cameras and dynamic control of pan-tilt-zoom (PTZ) cameras for optimal sensing; - Distributed processing and scene analysis algorithms; - Resource constraints imposed by different applications like security and surveillance, environmental monitoring, disaster response, assisted living facilities, etc. In this book, we focus on the basic research problems in camera networks, review the current state-of-the-art and present a detailed description of some of the recently developed methodologies. The major underlying theme in all the work presented is to take a network-centric view whereby the overall decisions are made at the network level. This is sometimes achieved by accumulating all the data at a central server, while at other times by exchanging decisions made by individual cameras based on their locally sensed data. Chapter One starts with an overview of the problems in camera networks and the major research directions. Some of the currently available experimental testbeds are also discussed here. One of the fundamental tasks in the analysis of dynamic scenes is to track objects. Since camera networks cover a large area, the systems need to be able to track over such wide areas where there could be both overlapping and non-overlapping fields of view of the cameras, as addressed in Chapter Two: Distributed processing is another challenge in camera networks and recent methods have shown how to do tracking, pose estimation and calibration in a distributed environment. Consensus algorithms that enable these tasks are described in Chapter Three. Chapter Four summarizes a few approaches on object and activity recognition in both distributed and centralized camera network environments. All these methods have focused primarily on the analysis side given that images are being obtained by the cameras. Efficient utilization of such networks often calls for active sensing, whereby the acquisition and analysis phases are closely linked. We discuss this issue in detail in Chapter Five and show how collaborative and opportunistic sensing in a camera network can be achieved. Finally, Chapter Six concludes the book by highlighting the major directions for future research. Table of Contents: An Introduction to Camera Networks / Wide-Area Tracking / Distributed Processing in Camera Networks / Object and Activity Recognition / Active Sensing / Future Research Directions

Activity Based Geometry Dependent Features for Information Processing in Heterogeneous Camera Networks

Activity Based Geometry Dependent Features for Information Processing in Heterogeneous Camera Networks Book
Author : Erhan Baki Ermiş
Publisher : Unknown
Release : 2010
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Abstract: Heterogeneous surveillance camera networks permit pervasive, wide-area visual surveillance for urban environments. However, due to the vast amounts of data they produce, human-operator monitoring is not possible and automatic algorithms are needed. In order to develop these automatic algorithms efficient and effective multi-camera information processing techniques must be developed. However, such multi-camera information processing techniques pose significant challenges in heterogeneous networks due to the fact that (i) most intuitive features used in video processing are geometric, i.e. utilize spatial information present in the video frames, (ii) the camera topology in heterogeneous networks is dynamic and cameras have significantly different observation geometries, consequently geometric features are not amenable to devising simple and efficient information processing techniques for heterogeneous networks. Based on these observations, we propose activity based behavior features that have certain geometry independence properties. Specifically, when the proposed features are used for information processing applications, a location observed by a number of cameras generates the same features across the cameras irrespective of their locations, orientations, and zoom levels. This geometry invariance property significantly simplifies the multi-camera information processing task in the sense that network's topology and camera calibration are no longer necessary to fuse information across cameras. We present applications of the proposed features to two such problems: (i) multi-camera correspondence, (ii) multi-camera anomaly detection. In the multi-camera correspondence application we use the activity features and propose a correspondence method that is robust to pose, illumination & geometric effects, and unsupervised (does not require any calibration objects to be utilized). In addition, through exploitation of sparsity of activity features combined with compressed sensing principles, we demonstrate that the proposed method is amenable to low communication bandwidth which is important for distributed systems. We present quantitative and qualitative results with synthetic and real life examples, which demonstrate that the proposed correspondence method outperforms methods that utilize geometric features when the cameras observe a scene with significantly different orientations. In the second application we consider the problem of abnormal behavior detection in heterogeneous networks, i.e., identification of objects whose behavior differs from behavior typically observed. We develop a framework that learns the behavior model at various regions of the video frames, and performs abnormal behavior detection via statistical methods. We show that due to the geometry independence property of the proposed features, models of normal activity obtained in one camera can be used as surrogate models in another camera to successfully perform anomaly detection. We present performance curves to demonstrate that in realistic urban monitoring scenarios, model training times can be significantly reduced when a new camera is added to a network of cameras. In both of these applications the main enabling principle is the geometry independence of the chosen features, which demonstrates how complex multi-camera information processing problems can be simplified by exploiting this principle. Finally, we present some statistical developments in the wider area of anomaly detection, which is motivated by the abnormal behavior detection application. We propose test statistics for detection problems with multidimensional observations and present optimality and robustness results.

Active Learning in Multi camera Networks with Applications in Person Re identification

Active Learning in Multi camera Networks  with Applications in Person Re identification Book
Author : Abir Das
Publisher : Unknown
Release : 2015
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

With the proliferation of cheap visual sensors, camera networks are everywhere. The ubiquitous presence of cameras opens the door for cutting edge research in processing and analysis of the huge video data generated by such large-scale camera networks. Re-identification of persons coming in and out of the cameras is an important task. This has remained a challenge to the community for a variety of reasons such as change of scale, illumination, resolution etc. between cameras. All these leads to transformation of features between cameras which makes re-identification a challenging task. The first question that is addressed in this work is - Can we model the way features get transformed between cameras and use it to our advantage to re-identify persons between cameras with non-overlapping views? The similarity between the feature histograms and time series data motivated us to apply the principle of Dynamic Time Warping to study the transformation of features by warping the feature space. After capturing the feature warps, describing the transformation of features the variabilities of the warp functions were modeled as a function space of these feature warps. The function space not only allowed us to model feasible transformation between pairs of instances of the same target, but also to separate them from the infeasible transformations between instances of different targets. A supervised training phase is employed to learn a discriminating surface between these two classes in the function space.

Distributed Video Sensor Networks

Distributed Video Sensor Networks Book
Author : Bir Bhanu,Chinya V. Ravishankar,Amit K. Roy-Chowdhury,Hamid Aghajan,Demetri Terzopoulos
Publisher : Springer Science & Business Media
Release : 2011-01-04
ISBN : 0857291270
Language : En, Es, Fr & De

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Book Description :

Large-scale video networks are of increasing importance in a wide range of applications. However, the development of automated techniques for aggregating and interpreting information from multiple video streams in real-life scenarios is a challenging area of research. Collecting the work of leading researchers from a broad range of disciplines, this timely text/reference offers an in-depth survey of the state of the art in distributed camera networks. The book addresses a broad spectrum of critical issues in this highly interdisciplinary field: current challenges and future directions; video processing and video understanding; simulation, graphics, cognition and video networks; wireless video sensor networks, communications and control; embedded cameras and real-time video analysis; applications of distributed video networks; and educational opportunities and curriculum-development. Topics and features: presents an overview of research in areas of motion analysis, invariants, multiple cameras for detection, object tracking and recognition, and activities in video networks; provides real-world applications of distributed video networks, including force protection, wide area activities, port security, and recognition in night-time environments; describes the challenges in graphics and simulation, covering virtual vision, network security, human activities, cognitive architecture, and displays; examines issues of multimedia networks, registration, control of cameras (in simulations and real networks), localization and bounds on tracking; discusses system aspects of video networks, with chapters on providing testbed environments, data collection on activities, new integrated sensors for airborne sensors, face recognition, and building sentient spaces; investigates educational opportunities and curriculum development from the perspective of computer science and electrical engineering. This unique text will be of great interest to researchers and graduate students of computer vision and pattern recognition, computer graphics and simulation, image processing and embedded systems, and communications, networks and controls. The large number of example applications will also appeal to application engineers.

Novel Traffic Sensing Using Multi camera Car Tracking and Re identification MCCTRI

Novel Traffic Sensing Using Multi camera Car Tracking and Re identification  MCCTRI  Book
Author : Hao Frank Yang
Publisher : Unknown
Release : 2020
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Traffic sensing devices are the eyes of the Intelligent Transportation Systems (ITS) nowadays. Among all the traffic sensors, the surveillance camera system is one of the most widely deployed system due to the easy installation, valuable data, and the intuitive information format. However, it's a great pity that these cameras collect data isolated. One camera can only monitor a fixed of view and there is no bridge to share the monitoring information with each other. Tremendous labor work is necessary if the traffic managers try to find the same target in different cameras. Recently, the development of computer vision technology brings light to traffic information extraction based on the multi-camera scenario. Different from the previous single-camera based traffic information estimation, the multi-camera work is much more challenging. Since in the real-world scenarios, different camera views, orientations and lighting conditions make the video features in a huge difference. Moreover, the more rigorous thing is that only the top-one candidate can be used in the traffic information estimation procedure. Thus, how to link each single camera into a multi-camera system and estimate the traffic information from the whole surveillance system becomes the main problem in the research. To address the challenges, four kinds of information are designed to capture and integrate, including vision information, vehicle attributes information, road network graph information and spatial-temporal information. These four kinds of information are summarized and decomposed into four levels of features, including frame-level, clip-level, identity-level and network-level of features. A cutting-edge multi-camera car tracking and Re-ID framework based on temporal-attention model and deep neural networks is improved to capture the frame-level, clip-level and identity-level of features. A Spatial-temporal Camera Graph Inference Model (StCGIM) are designed to integrate the network level of features into the MCCTRI framework. After obtained the multi-camera tracking result, the tracking accuracy levels of different cameras are various from each other. An Adaptative Accuracy Model (AAM) is designed to eliminate and unify errors and prepare the input for the traffic information estimation algorithms. Furthermore, different levels of traffic-related information can be estimated properly. The author evaluated the framework based on five cameras video data on captured on the Interstate 5, including different views, orientations, lighting conditions and color settings in various challenging scenarios. Based on MCCTRI, not only including the traffic information value, such as link average speed, average travel time and volume, but also a more particular data format 0́3 the distribution of each parameter can be estimated precisely. All the value information estimation error is less than 8% through the dataset evaluation including five camera views. The KL distance of the estimated distribution and real distribution is less than 3.42. Based on the experiment, the MCCTRI gives the surveillance camera system a brain and more precise and valuable information can be extracted through the method.

Robust Video Object Tracking in Distributed Camera Networks

Robust Video Object Tracking in Distributed Camera Networks Book
Author : Younggun Lee
Publisher : Unknown
Release : 2017
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

We propose a robust video object tracking system in distributed camera networks. The main problem associated with wide-area surveillance is people to be tracked may exhibit dramatic changes on account of varied illuminations, viewing angles, poses and camera responses, under different cameras. We intend to construct a robust human tracking system across multiple cameras based on fully unsupervised online learning so that the camera link models among them can be learned online, and the tracked targets in every single camera can be accurately re-identified with both appearance cue and context information. We present three main parts of our research: an ensemble of invariant appearance descriptors, inter-camera tracking based on fully unsupervised online learning, and multiple-camera human tracking across non-overlapping cameras. As for effective appearance descriptors, we present an appearance-based re-id framework, which uses an ensemble of invariant features to achieve robustness against partial occlusion, camera color response variation, and pose and viewpoint changes, etc. The proposed method not only solves the problems resulted from the changing human pose and viewpoint, with some tolerance of illumination changes but also can skip the laborious calibration effort and restriction. We take an advantage of effective invariant features proposed above in the tracking. We present an inter-camera tracking method based on online learning, which systematically builds camera link model without any human intervention. The aim of inter-camera tracking is to assign unique IDs when people move across different cameras. Facilitated by the proposed two-phase feature extractor, which consists of two-way Gaussian mixture model fitting and couple features in phase I, followed by the holistic color, regional color/texture features in phase II, the proposed method can effectively and robustly identify the same person across cameras. To build the complete tracking system, we propose a robust multiple-camera tracking system based on a two-step framework, the single-camera tracking algorithm is firstly performed in each camera to create trajectories of multi-targets, and then the inter-camera tracking algorithm is carried out to associate the tracks belonging to the same identity. Since inter-camera tracking algorithms derive the appearance and motion features by using single-camera tracking results, i.e., detected/tracked object and segmentation mask, inter-camera tracking performance highly depends on single-camera tracking performance. For single-camera tracking, we present multi-object tracking within a single camera that can adaptively refine the segmentation results based on multi-kernel feedback from preliminary tracking to handle the problems of object merging and shadowing. Besides, detection in local object region is incorporated to address initial occlusion when people appear in groups.

Intelligent Robotics and Applications

Intelligent Robotics and Applications Book
Author : Honghai Liu,Han Ding,Zhenhua Xiong,Xiangyang Zhu
Publisher : Springer
Release : 2010-11-18
ISBN : 3642165842
Language : En, Es, Fr & De

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Book Description :

The market demand for skills, knowledge and adaptability have positioned robotics to be an important field in both engineering and science. One of the most highly visible applications of robotics has been the robotic automation of many industrial tasks in factories. In the future, a new era will come in which we will see a greater success for robotics in non-industrial environments. In order to anticipate a wider deployment of intelligent and autonomous robots for tasks such as manufacturing, healthcare, ent- tainment, search and rescue, surveillance, exploration, and security missions, it is essential to push the frontier of robotics into a new dimension, one in which motion and intelligence play equally important roles. The 2010 International Conference on Intelligent Robotics and Applications (ICIRA 2010) was held in Shanghai, China, November 10–12, 2010. The theme of the c- ference was “Robotics Harmonizing Life,” a theme that reflects the ever-growing interest in research, development and applications in the dynamic and exciting areas of intelligent robotics. These volumes of Springer’s Lecture Notes in Artificial Intel- gence and Lecture Notes in Computer Science contain 140 high-quality papers, which were selected at least for the papers in general sessions, with a 62% acceptance rate Traditionally, ICIRA 2010 holds a series of plenary talks, and we were fortunate to have two such keynote speakers who shared their expertise with us in diverse topic areas spanning the rang of intelligent robotics and application activities.

Game Theory for Wireless Communications and Networking

Game Theory for Wireless Communications and Networking Book
Author : Yan Zhang,MOHSEN GUIZANI
Publisher : CRC Press
Release : 2011-06-23
ISBN : 1439808910
Language : En, Es, Fr & De

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Book Description :

Used to explain complicated economic behavior for decades, game theory is quickly becoming a tool of choice for those serious about optimizing next generation wireless systems. Illustrating how game theory can effectively address a wide range of issues that until now remained unresolved, Game Theory for Wireless Communications and Networking provid

Self Calibration of Multi Camera Systems

Self Calibration of Multi Camera Systems Book
Author : Ferid Bajramovic
Publisher : Logos Verlag Berlin GmbH
Release : 2010
ISBN : 3832527362
Language : En, Es, Fr & De

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Book Description :

Multi-camera systems play an increasingly important role in computer vision. They enable applications like 3D video reconstruction, motion capture, smart homes, wide area surveillance, etc. Most of these require or benefit from a calibration of the multi-camera system. This book presents a novel approach for automatically estimating that calibration. In contrast to established methods, it neither requires a calibration object nor any user interaction. From a theoretical point of view, this book also presents and solves the novel graph theoretical problem of finding shortest triangle paths.

Wireless Multimedia Sensor Networks on Reconfigurable Hardware

Wireless Multimedia Sensor Networks on Reconfigurable Hardware Book
Author : Li-minn Ang,Kah Phooi Seng,Li Wern Chew,Lee Seng Yeong,Wai Chong Chia
Publisher : Springer Science & Business Media
Release : 2013-11-19
ISBN : 3642382037
Language : En, Es, Fr & De

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Book Description :

Traditional wireless sensor networks (WSNs) capture scalar data such as temperature, vibration, pressure, or humidity. Motivated by the success of WSNs and also with the emergence of new technology in the form of low-cost image sensors, researchers have proposed combining image and audio sensors with WSNs to form wireless multimedia sensor networks (WMSNs). This introduces practical and research challenges, because multimedia sensors, particularly image sensors, generate huge amounts of data to be processed and distributed within the network, while sensor nodes have restricted battery power and hardware resources. This book describes how reconfigurable hardware technologies such as field-programmable gate arrays (FPGAs) offer cost-effective, flexible platforms for implementing WMSNs, with a main focus on developing efficient algorithms and architectures for information reduction, including event detection, event compression, and multicamera processing for hardware implementations. The authors include a comprehensive review of wireless multimedia sensor networks, a complete specification of a very low-complexity, low-memory FPGA WMSN node processor, and several case studies that illustrate information reduction algorithms for visual event compression, detection, and fusion. The book will be of interest to academic researchers, R&D engineers, and computer science and engineering graduate students engaged with signal and video processing, computer vision, embedded systems, and sensor networks.

Image Analysis and Processing ICIAP 2015

Image Analysis and Processing     ICIAP 2015 Book
Author : Vittorio Murino,Enrico Puppo
Publisher : Springer
Release : 2015-08-20
ISBN : 3319232312
Language : En, Es, Fr & De

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Book Description :

The two-volume set LNCS 9279 and 9280 constitutes the refereed proceedings of the 18th International Conference on Image Analysis and Processing, ICIAP 2015, held in Genoa, Italy, in September 2015. The 129 papers presented were carefully reviewed and selected from 231 submissions. The papers are organized in the following seven topical sections: video analysis and understanding, multiview geometry and 3D computer vision, pattern recognition and machine learning, image analysis, detection and recognition, shape analysis and modeling, multimedia, and biomedical applications.

Advanced Concepts for Intelligent Vision Systems

Advanced Concepts for Intelligent Vision Systems Book
Author : Sebastiano Battiato,Jacques Blanc-Talon,Giovanni Gallo,Wilfried Philips,Dan Popescu,Paul Scheunders
Publisher : Springer
Release : 2015-10-07
ISBN : 3319259032
Language : En, Es, Fr & De

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Book Description :

This book constitutes the thoroughly refereed proceedings of the 16th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2015, held Catania, Italy, in October 2015. The 76 revised full papers were carefully selected from 129 submissions. Acivs 2015 is a conference focusing on techniques for building adaptive, intelligent, safe and secure imaging systems. The focus of the conference is on following topic: low-level Image processing, video processing and camera networks, motion and tracking, security, forensics and biometrics, depth and 3D, image quality improvement and assessment, classification and recognition, multidimensional signal processing, multimedia compression, retrieval, and navigation.

Advanced Concepts for Intelligent Vision Systems

Advanced Concepts for Intelligent Vision Systems Book
Author : Jacques Blanc-Talon,Don Bone,Wilfried Philips,Dan Popescu,Paul Scheunders
Publisher : Springer
Release : 2010-12-06
ISBN : 3642176917
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed proceedings of the 12th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2010, held in Changchun, China, in August 2010. The 78 revised full papers presented were carefully reviewed and selected from 144 submissions. The papers are organized in topical sections on image processing and analysis; segmentation and edge detection; 3D and depth; algorithms and optimizations; video processing; surveillance and camera networks; machine vision; remote sensing; and recognition, classification and tracking.

Academic Press Library in Signal Processing

Academic Press Library in Signal Processing Book
Author : Anonim
Publisher : Academic Press
Release : 2013-09-14
ISBN : 0123972256
Language : En, Es, Fr & De

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Book Description :

This fourth volume, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in Image, Video Processing and Analysis, Hardware, Audio, Acoustic and Speech Processing. With this reference source you will: Quickly grasp a new area of research Understand the underlying principles of a topic and its application Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved Quick tutorial reviews of important and emerging topics of research in Image, Video Processing and Analysis, Hardware, Audio, Acoustic and Speech Processing Presents core principles and shows their application Reference content on core principles, technologies, algorithms and applications Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic

Self aware Computing Systems

Self aware Computing Systems Book
Author : Peter R. Lewis,Marco Platzner,Bernhard Rinner,Jim Tørresen,Xin Yao
Publisher : Springer
Release : 2016-07-28
ISBN : 3319396757
Language : En, Es, Fr & De

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Book Description :

Taking inspiration from self-awareness in humans, this book introduces the new notion of computational self-awareness as a fundamental concept for designing and operating computing systems. The basic ability of such self-aware computing systems is to collect information about their state and progress, learning and maintaining models containing knowledge that enables them to reason about their behaviour. Self-aware computing systems will have the ability to utilise this knowledge to effectively and autonomously adapt and explain their behaviour, in changing conditions. This book addresses these fundamental concepts from an engineering perspective, aiming at developing primitives for building systems and applications. It will be of value to researchers, professionals and graduate students in computer science and engineering.

GeoSensor Networks

GeoSensor Networks Book
Author : Silvia Nittel
Publisher : Springer Science & Business Media
Release : 2008-08-04
ISBN : 3540799958
Language : En, Es, Fr & De

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Book Description :

This book constitutes the thoroughly refereed proceedings of the Second GeoSensor Networks Conference, held in Boston, Massachusetts, USA, in October 2006. The conference addressed issues related to the collection, management, processing, analysis, and delivery of real-time geospatial data using distributed geosensor networks. This represents an evolution of the traditional static and centralized geocomputational paradigm. The 13 carefully reviewed and selected papers included in the volume constitute extended versions of the papers presented at the conference. They are preceded by an introduction written by the volume editors. The book is structured in sections on Data Acquisition and Processing, Data Analysis and Integration, and Applications. The papers represent key research areas that are fundamental in order to realize the full potential of the emerging geosensor network paradigm. The contributions cover theentire spectrum of the field from low-level energy consumption issues at the individual sensor level to the high-level abstraction of events and ontologies or models to recognize and monitor phenomena using geosensor networks.