Object Tracking Technology

Object Tracking Technology
Author :
Publisher : Springer Nature
Total Pages : 280
Release :
ISBN-10 : 9789819932887
ISBN-13 : 9819932882
Rating : 4/5 (87 Downloads)

Synopsis Object Tracking Technology by : Ashish Kumar

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

Object Detection and Recognition in Digital Images
Author :
Publisher : John Wiley & Sons
Total Pages : 518
Release :
ISBN-10 : 9781118618363
ISBN-13 : 111861836X
Rating : 4/5 (63 Downloads)

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

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.

Digital Visual Effects and Compositing

Digital Visual Effects and Compositing
Author :
Publisher : Pearson Education
Total Pages : 553
Release :
ISBN-10 : 9780321984388
ISBN-13 : 0321984382
Rating : 4/5 (88 Downloads)

Synopsis Digital Visual Effects and Compositing by : Jon Gress

Annotation Everything you need to know to become a professional VFX whizz in one thorough and comprehensive guide.

Fundamentals of Object Tracking

Fundamentals of Object Tracking
Author :
Publisher : Cambridge University Press
Total Pages : 389
Release :
ISBN-10 : 9780521876285
ISBN-13 : 0521876281
Rating : 4/5 (85 Downloads)

Synopsis Fundamentals of Object Tracking by :

Introduces object tracking algorithms from a unified, recursive Bayesian perspective, along with performance bounds and illustrative examples.

Video-Based Surveillance Systems

Video-Based Surveillance Systems
Author :
Publisher : Springer Science & Business Media
Total Pages : 277
Release :
ISBN-10 : 9781461509134
ISBN-13 : 1461509130
Rating : 4/5 (34 Downloads)

Synopsis Video-Based Surveillance Systems by : Graeme A. Jones

Monitoring of public and private sites has increasingly become a very sensitive issue resulting in a patchwork of privacy laws varying from country to country -though all aimed at protecting the privacy of the citizen. It is important to remember, however, that monitoring and vi sual surveillance capabilities can also be employed to aid the citizen. The focus of current development is primarily aimed at public and cor porate safety applications including the monitoring of railway stations, airports, and inaccessible or dangerous environments. Future research effort, however, has already targeted citizen-oriented applications such as monitoring assistants for the aged and infirm, route-planning and congestion-avoidance tools, and a range of environment al monitoring applications. The latest generation of surveillance systems has eagerly adopted re cent technological developments to produce a fully digital pipeline of digital image acquisition, digital data transmission and digital record ing. The resultant surveillance products are highly-fiexihle, capahle of generating forensic-quality imagery, and ahle to exploit existing Internet and wide area network services to provide remote monitoring capability.

Examining the Impact of Deep Learning and IoT on Multi-Industry Applications

Examining the Impact of Deep Learning and IoT on Multi-Industry Applications
Author :
Publisher : IGI Global
Total Pages : 304
Release :
ISBN-10 : 9781799875178
ISBN-13 : 1799875172
Rating : 4/5 (78 Downloads)

Synopsis Examining the Impact of Deep Learning and IoT on Multi-Industry Applications by : Raut, Roshani

Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings. Examining the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers’ points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.

Moving Object Detection Using Background Subtraction

Moving Object Detection Using Background Subtraction
Author :
Publisher : Springer
Total Pages : 74
Release :
ISBN-10 : 9783319073866
ISBN-13 : 3319073869
Rating : 4/5 (66 Downloads)

Synopsis Moving Object Detection Using Background Subtraction by : Soharab Hossain Shaikh

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.

Visual Object Tracking using Deep Learning

Visual Object Tracking using Deep Learning
Author :
Publisher : CRC Press
Total Pages : 216
Release :
ISBN-10 : 9781000990980
ISBN-13 : 1000990982
Rating : 4/5 (80 Downloads)

Synopsis Visual Object Tracking using Deep Learning by : Ashish Kumar

This book covers the description of both conventional methods and advanced methods. In conventional methods, visual tracking techniques such as stochastic, deterministic, generative, and discriminative are discussed. The conventional techniques are further explored for multi-stage and collaborative frameworks. In advanced methods, various categories of deep learning-based trackers and correlation filter-based trackers are analyzed. The book also: Discusses potential performance metrics used for comparing the efficiency and effectiveness of various visual tracking methods Elaborates on the salient features of deep learning trackers along with traditional trackers, wherein the handcrafted features are fused to reduce computational complexity Illustrates various categories of correlation filter-based trackers suitable for superior and efficient performance under tedious tracking scenarios Explores the future research directions for visual tracking by analyzing the real-time applications The book comprehensively discusses various deep learning-based tracking architectures along with conventional tracking methods. It covers in-depth analysis of various feature extraction techniques, evaluation metrics and benchmark available for performance evaluation of tracking frameworks. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

Visual Object Tracking from Correlation Filter to Deep Learning

Visual Object Tracking from Correlation Filter to Deep Learning
Author :
Publisher : Springer Nature
Total Pages : 202
Release :
ISBN-10 : 9789811662423
ISBN-13 : 9811662428
Rating : 4/5 (23 Downloads)

Synopsis Visual Object Tracking from Correlation Filter to Deep Learning by : Weiwei Xing

The book focuses on visual object tracking systems and approaches based on correlation filter and deep learning. Both foundations and implementations have been addressed. The algorithm, system design and performance evaluation have been explored for three kinds of tracking methods including correlation filter based methods, correlation filter with deep feature based methods, and deep learning based methods. Firstly, context aware and multi-scale strategy are presented in correlation filter based trackers; then, long-short term correlation filter, context aware correlation filter and auxiliary relocation in SiamFC framework are proposed for combining correlation filter and deep learning in visual object tracking; finally, improvements in deep learning based trackers including Siamese network, GAN and reinforcement learning are designed. The goal of this book is to bring, in a timely fashion, the latest advances and developments in visual object tracking, especially correlation filter and deep learning based methods, which is particularly suited for readers who are interested in the research and technology innovation in visual object tracking and related fields.

Visual Object Tracking with Deep Neural Networks

Visual Object Tracking with Deep Neural Networks
Author :
Publisher : BoD – Books on Demand
Total Pages : 208
Release :
ISBN-10 : 9781789851571
ISBN-13 : 1789851572
Rating : 4/5 (71 Downloads)

Synopsis Visual Object Tracking with Deep Neural Networks by : Pier Luigi Mazzeo

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.