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Machine Learning For Human Motion Analysis Theory And Practice
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Book Synopsis Machine Learning for Human Motion Analysis: Theory and Practice by : Wang, Liang
Download or read book Machine Learning for Human Motion Analysis: Theory and Practice written by Wang, Liang and published by IGI Global. This book was released on 2009-12-31 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book highlights the development of robust and effective vision-based motion understanding systems, addressing specific vision applications such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval"--Provided by publisher.
Book Synopsis Machine Learning for Vision-Based Motion Analysis by : Liang Wang
Download or read book Machine Learning for Vision-Based Motion Analysis written by Liang Wang and published by Springer Science & Business Media. This book was released on 2010-11-18 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine interfaces, the ability to automatically analyze and understand object motions from video footage is of increasing importance. Among the latest developments in this field is the application of statistical machine learning algorithms for object tracking, activity modeling, and recognition. Developed from expert contributions to the first and second International Workshop on Machine Learning for Vision-Based Motion Analysis, this important text/reference highlights the latest algorithms and systems for robust and effective vision-based motion understanding from a machine learning perspective. Highlighting the benefits of collaboration between the communities of object motion understanding and machine learning, the book discusses the most active forefronts of research, including current challenges and potential future directions. Topics and features: provides a comprehensive review of the latest developments in vision-based motion analysis, presenting numerous case studies on state-of-the-art learning algorithms; examines algorithms for clustering and segmentation, and manifold learning for dynamical models; describes the theory behind mixed-state statistical models, with a focus on mixed-state Markov models that take into account spatial and temporal interaction; discusses object tracking in surveillance image streams, discriminative multiple target tracking, and guidewire tracking in fluoroscopy; explores issues of modeling for saliency detection, human gait modeling, modeling of extremely crowded scenes, and behavior modeling from video surveillance data; investigates methods for automatic recognition of gestures in Sign Language, and human action recognition from small training sets. Researchers, professional engineers, and graduate students in computer vision, pattern recognition and machine learning, will all find this text an accessible survey of machine learning techniques for vision-based motion analysis. The book will also be of interest to all who work with specific vision applications, such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval.
Book Synopsis Machine Learning Approaches to Human Movement Analysis by : Matteo Zago
Download or read book Machine Learning Approaches to Human Movement Analysis written by Matteo Zago and published by Frontiers Media SA. This book was released on 2021-03-04 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Deep Learning for Human Motion Analysis by : Natalia Neverova (informaticienne).)
Download or read book Deep Learning for Human Motion Analysis written by Natalia Neverova (informaticienne).) and published by . This book was released on 2020 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: The research goal of this work is to develop learning methods advancing automatic analysis and interpreting of human motion from different perspectives and based on various sources of information, such as images, video, depth, mocap data, audio and inertial sensors. For this purpose, we propose a several deep neural models and associated training algorithms for supervised classification and semi-supervised feature learning, as well as modelling of temporal dependencies, and show their efficiency on a set of fundamental tasks, including detection, classification, parameter estimation and user verification. First, we present a method for human action and gesture spotting and classification based on multi-scale and multi-modal deep learning from visual signals (such as video, depth and mocap data). Key to our technique is a training strategy which exploits, first, careful initialization of individual modalities and, second, gradual fusion involving random dropping of separate channels (dubbed ModDrop) for learning cross-modality correlations while preserving uniqueness of each modality-specific representation. Moving forward, from 1 to N mapping to continuous evaluation of gesture parameters, we address the problem of hand pose estimation and present a new method for regression on depth images, based on semi-supervised learning using convolutional deep neural networks, where raw depth data is fused with an intermediate representation in the form of a segmentation of the hand into parts. In separate but related work, we explore convolutional temporal models for human authentication based on their motion patterns. In this project, the data is captured by inertial sensors (such as accelerometers and gyroscopes) built in mobile devices. We propose an optimized shift-invariant dense convolutional mechanism and incorporate the discriminatively-trained dynamic features in a probabilistic generative framework taking into account temporal characteristics. Our results demonstrate, that human kinematics convey important information about user identity and can serve as a valuable component of multi-modal authentication systems.
Book Synopsis Human Motion Sensing and Recognition by : Honghai Liu
Download or read book Human Motion Sensing and Recognition written by Honghai Liu and published by Springer. This book was released on 2017-05-11 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces readers to the latest exciting advances in human motion sensing and recognition, from the theoretical development of fuzzy approaches to their applications. The topics covered include human motion recognition in 2D and 3D, hand motion analysis with contact sensors, and vision-based view-invariant motion recognition, especially from the perspective of Fuzzy Qualitative techniques. With the rapid development of technologies in microelectronics, computers, networks, and robotics over the last decade, increasing attention has been focused on human motion sensing and recognition in many emerging and active disciplines where human motions need to be automatically tracked, analyzed or understood, such as smart surveillance, intelligent human-computer interaction, robot motion learning, and interactive gaming. Current challenges mainly stem from the dynamic environment, data multi-modality, uncertain sensory information, and real-time issues. These techniques are shown to effectively address the above challenges by bridging the gap between symbolic cognitive functions and numerical sensing & control tasks in intelligent systems. The book not only serves as a valuable reference source for researchers and professionals in the fields of computer vision and robotics, but will also benefit practitioners and graduates/postgraduates seeking advanced information on fuzzy techniques and their applications in motion analysis.
Book Synopsis Encyclopedia of Data Science and Machine Learning by : Wang, John
Download or read book Encyclopedia of Data Science and Machine Learning written by Wang, John and published by IGI Global. This book was released on 2023-01-20 with total page 3296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
Book Synopsis Modelling Human Motion by : Nicoletta Noceti
Download or read book Modelling Human Motion written by Nicoletta Noceti and published by Springer Nature. This book was released on 2020-07-09 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new frontiers of robotics research foresee future scenarios where artificial agents will leave the laboratory to progressively take part in the activities of our daily life. This will require robots to have very sophisticated perceptual and action skills in many intelligence-demanding applications, with particular reference to the ability to seamlessly interact with humans. It will be crucial for the next generation of robots to understand their human partners and at the same time to be intuitively understood by them. In this context, a deep understanding of human motion is essential for robotics applications, where the ability to detect, represent and recognize human dynamics and the capability for generating appropriate movements in response sets the scene for higher-level tasks. This book provides a comprehensive overview of this challenging research field, closing the loop between perception and action, and between human-studies and robotics. The book is organized in three main parts. The first part focuses on human motion perception, with contributions analyzing the neural substrates of human action understanding, how perception is influenced by motor control, and how it develops over time and is exploited in social contexts. The second part considers motion perception from the computational perspective, providing perspectives on cutting-edge solutions available from the Computer Vision and Machine Learning research fields, addressing higher-level perceptual tasks. Finally, the third part takes into account the implications for robotics, with chapters on how motor control is achieved in the latest generation of artificial agents and how such technologies have been exploited to favor human-robot interaction. This book considers the complete human-robot cycle, from an examination of how humans perceive motion and act in the world, to models for motion perception and control in artificial agents. In this respect, the book will provide insights into the perception and action loop in humans and machines, joining together aspects that are often addressed in independent investigations. As a consequence, this book positions itself in a field at the intersection of such different disciplines as Robotics, Neuroscience, Cognitive Science, Psychology, Computer Vision, and Machine Learning. By bridging these different research domains, the book offers a common reference point for researchers interested in human motion for different applications and from different standpoints, spanning Neuroscience, Human Motor Control, Robotics, Human-Robot Interaction, Computer Vision and Machine Learning. Chapter 'The Importance of the Affective Component of Movement in Action Understanding' of this book is available open access under a CC BY 4.0 license at link.springer.com.
Book Synopsis Intelligent Data Analysis for Real-Life Applications: Theory and Practice by : Magdalena-Benedito, Rafael
Download or read book Intelligent Data Analysis for Real-Life Applications: Theory and Practice written by Magdalena-Benedito, Rafael and published by IGI Global. This book was released on 2012-06-30 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the recent and enormous increase in the amount of available data sets of all kinds, applying effective and efficient techniques for analyzing and extracting information from that data has become a crucial task. Intelligent Data Analysis for Real-Life Applications: Theory and Practice investigates the application of Intelligent Data Analysis (IDA) to these data sets through the design and development of algorithms and techniques to extract knowledge from databases. This pivotal reference explores practical applications of IDA, and it is essential for academic and research libraries as well as students, researchers, and educators in data analysis, application development, and database management.
Book Synopsis Background Subtraction by : Ahmed Elgammal
Download or read book Background Subtraction written by Ahmed Elgammal and published by Morgan & Claypool Publishers. This book was released on 2014-12-01 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: Background subtraction is a widely used concept for detection of moving objects in videos. In the last two decades there has been a lot of development in designing algorithms for background subtraction, as well as wide use of these algorithms in various important applications, such as visual surveillance, sports video analysis, motion capture, etc. Various statistical approaches have been proposed to model scene backgrounds. The concept of background subtraction also has been extended to detect objects from videos captured from moving cameras. This book reviews the concept and practice of background subtraction. We discuss several traditional statistical background subtraction models, including the widely used parametric Gaussian mixture models and non-parametric models. We also discuss the issue of shadow suppression, which is essential for human motion analysis applications. This book discusses approaches and tradeoffs for background maintenance. This book also reviews many of the recent developments in background subtraction paradigm. Recent advances in developing algorithms for background subtraction from moving cameras are described, including motion-compensation-based approaches and motion-segmentation-based approaches.
Book Synopsis Application of Intelligent Systems in Multi-modal Information Analytics by : Vijayan Sugumaran
Download or read book Application of Intelligent Systems in Multi-modal Information Analytics written by Vijayan Sugumaran and published by Springer Nature. This book was released on 2021-04-16 with total page 970 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides comprehensive coverage of the latest advances and trends in information technology, science and engineering. Specifically, it addresses a number of broad themes, including multi-modal informatics, data mining, agent-based and multi-agent systems for health and education informatics, which inspire the development of intelligent information technologies. The contributions cover a wide range of topics such as AI applications and innovations in health and education informatics; data and knowledge management; multi-modal application management; and web/social media mining for multi-modal informatics. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals, and a useful reference guide for newcomers to the field. This book is a compilation of the papers presented in the 2021 International Conference on Multi-modal Information Analytics, held in Huhehaote, China, on April 23–24, 2021.
Book Synopsis Data Analytics and Applications of the Wearable Sensors in Healthcare by : Shabbir Syed-Abdul
Download or read book Data Analytics and Applications of the Wearable Sensors in Healthcare written by Shabbir Syed-Abdul and published by MDPI. This book was released on 2020-06-17 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a collection of comprehensive research articles on data analytics and applications of wearable devices in healthcare. This Special Issue presents 28 research studies from 137 authors representing 37 institutions from 19 countries. To facilitate the understanding of the research articles, we have organized the book to show various aspects covered in this field, such as eHealth, technology-integrated research, prediction models, rehabilitation studies, prototype systems, community health studies, ergonomics design systems, technology acceptance model evaluation studies, telemonitoring systems, warning systems, application of sensors in sports studies, clinical systems, feasibility studies, geographical location based systems, tracking systems, observational studies, risk assessment studies, human activity recognition systems, impact measurement systems, and a systematic review. We would like to take this opportunity to invite high quality research articles for our next Special Issue entitled “Digital Health and Smart Sensors for Better Management of Cancer and Chronic Diseases” as a part of Sensors journal.
Book Synopsis Learning-based Inverse Dynamics for Human Motion Analysis by : Petrissa Zell
Download or read book Learning-based Inverse Dynamics for Human Motion Analysis written by Petrissa Zell and published by . This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Automated Multi-Camera Surveillance by : Omar Javed
Download or read book Automated Multi-Camera Surveillance written by Omar Javed and published by Springer Science & Business Media. This book was released on 2008-12-16 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent development of intelligent surveillance systems has captured the interest of both academic research labs and industry. Automated Multi-Camera Surveillance addresses monitoring of people and vehicles, and detection of threatening objects and events in a variety of scenarios. In this book, techniques for development of an automated multi-camera surveillance system are discussed and proposed. The state-of-the-art in the automated surveillance systems is reviewed as well. Detailed explanation of sub-components of surveillance systems are provided, and enhancements to each of these components are proposed. The authors identify important challenges that such a system must address, and propose solutions. Development of a specific surveillance system called “KNIGHT” is described, along with the authors’ experience using it. This book enables the reader to understand the mathematical models and algorithms underlying automated surveillance as well as the benefits and limitations of using such methods.
Author :Md. Atiqur Rahman Ahad Publisher :Springer Science & Business Media ISBN 13 :9491216201 Total Pages :211 pages Book Rating :4.4/5 (912 download)
Book Synopsis Computer Vision and Action Recognition by : Md. Atiqur Rahman Ahad
Download or read book Computer Vision and Action Recognition written by Md. Atiqur Rahman Ahad and published by Springer Science & Business Media. This book was released on 2011-12-02 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human action analyses and recognition are challenging problems due to large variations in human motion and appearance, camera viewpoint and environment settings. The field of action and activity representation and recognition is relatively old, yet not well-understood by the students and research community. Some important but common motion recognition problems are even now unsolved properly by the computer vision community. However, in the last decade, a number of good approaches are proposed and evaluated subsequently by many researchers. Among those methods, some methods get significant attention from many researchers in the computer vision field due to their better robustness and performance. This book will cover gap of information and materials on comprehensive outlook – through various strategies from the scratch to the state-of-the-art on computer vision regarding action recognition approaches. This book will target the students and researchers who have knowledge on image processing at a basic level and would like to explore more on this area and do research. The step by step methodologies will encourage one to move forward for a comprehensive knowledge on computer vision for recognizing various human actions.
Book Synopsis Statistical Machine Learning for Human Behaviour Analysis by : Thomas Moeslund
Download or read book Statistical Machine Learning for Human Behaviour Analysis written by Thomas Moeslund and published by MDPI. This book was released on 2020-06-17 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Special Issue focused on novel vision-based approaches, mainly related to computer vision and machine learning, for the automatic analysis of human behaviour. We solicited submissions on the following topics: information theory-based pattern classification, biometric recognition, multimodal human analysis, low resolution human activity analysis, face analysis, abnormal behaviour analysis, unsupervised human analysis scenarios, 3D/4D human pose and shape estimation, human analysis in virtual/augmented reality, affective computing, social signal processing, personality computing, activity recognition, human tracking in the wild, and application of information-theoretic concepts for human behaviour analysis. In the end, 15 papers were accepted for this special issue. These papers, that are reviewed in this editorial, analyse human behaviour from the aforementioned perspectives, defining in most of the cases the state of the art in their corresponding field.
Book Synopsis Human Motion - Understanding, Modeling, Capture and Animation by : Ahmed Elgammal
Download or read book Human Motion - Understanding, Modeling, Capture and Animation written by Ahmed Elgammal and published by Springer. This book was released on 2007-11-15 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second Workshop on Human Motion, HumanMotion 2007, held in Rio de Janeiro, Brazil October 2007 in conjunction with ICCV 2007. The 22 revised full papers presented were carefully reviewed and selected from 38 submissions. The papers are organized in topical sections on motion capture and pose estimation, body and limb tracking and segmentation and activity recognition.
Download or read book Video Tracking written by Emilio Maggio and published by John Wiley & Sons. This book was released on 2011-07-05 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Video Tracking provides a comprehensive treatment of the fundamental aspects of algorithm and application development for the task of estimating, over time, the position of objects of interest seen through cameras. Starting from the general problem definition and a review of existing and emerging video tracking applications, the book discusses popular methods, such as those based on correlation and gradient-descent. Using practical examples, the reader is introduced to the advantages and limitations of deterministic approaches, and is then guided toward more advanced video tracking solutions, such as those based on the Bayes’ recursive framework and on Random Finite Sets. Key features: Discusses the design choices and implementation issues required to turn the underlying mathematical models into a real-world effective tracking systems. Provides block diagrams and simil-code implementation of the algorithms. Reviews methods to evaluate the performance of video trackers – this is identified as a major problem by end-users. The book aims to help researchers and practitioners develop techniques and solutions based on the potential of video tracking applications. The design methodologies discussed throughout the book provide guidelines for developers in the industry working on vision-based applications. The book may also serve as a reference for engineering and computer science graduate students involved in vision, robotics, human-computer interaction, smart environments and virtual reality programmes
