Human Activity Analysis In Visual Surveillance And Healthcare

An automatic recognition of human activities enables their use in several interesting applications of daily life. This dissertation emphases on the analysis of human activities in a visual surveillance scenario and the classification of physical activities in the therapeutic procedure using visual data. The first part of the dissertation proposes a robust gait representation to recognise the identity of a person using his/her walking style, dealing with its several real world challenges as well as taking into consideration the effects of cross-view recognition. In the second part, a complete framework is proposed to capture and analyse the movement of different body parts in human which is useful in the clinical assessment to detect any movement disorders and the assessment of the desired therapeutic program.

This book is a truly comprehensive, timely, and very much needed treatise on the conceptualization of analysis, and design of contactless & multimodal sensor-based human activities, behavior understanding & intervention. From an interaction design perspective, the book provides views and methods that allow for more safe, trustworthy, efficient, and more natural interaction with technology that will be embedded in our daily living environments. The chapters in this book cover sufficient grounds and depth in related challenges and advances in sensing, signal processing, computer vision, and mathematical modeling. It covers multi-domain applications, including surveillance and elderly care that will be an asset to entry-level and practicing engineers and scientists.(See inside for the reviews from top experts)

Cardiovascular disease has become the number one cause of death worldwide. For the diagnosis and therapy of coronary artery disease, interventional C-arm-based fluoroscopy is an imaging method of choice. While these C-arm systems are also capable of rotating around the patient and thus allow a CT-like 3-D image reconstruction, their long rotation time of about five seconds leads to strong motion artefacts in 3-D coronary artery imaging. In this work, a novel method is introduced that is based on a 2-D-2-D image registration algorithm. It is embedded in an iterative algorithm for motion estimation and compensation and does not require any complex segmentation or user interaction. It is thus fully automatic, which is a very desirable feature for interventional applications. The method is evaluated on simulated and human clinical data. Overall, it could be shown that the method can be successfully applied to a large set of clinical data without user interaction or parameter changes, and with a high robustness against initial 3-D image quality, while delivering results that are at least up to the current state of the art, and better in many cases.

This book includes high-quality research papers presented at the 1st International Conference on Wireless Sensor Networks, Ubiquitous Computing and Applications (ICWSNUCA, 2021), which is held at Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, India, during 26–27 February, 2021. This volume focuses on the applications, use-cases, architectures, deployments, and recent advances of wireless sensor networks as well as ubiquious computing. Different research topics are illustrated in this book, like wireless sensor networks for the Internet of Things; IoT applications for eHealth; smart cities; architectures for WSNs and IoT, WSNs hardware and new devices; low-power wireless technologies; wireless ad hoc sensor networks; routing and data transfer in WSNs; multicast communication in WSNs; security management in WSNs and in IoT systems; and power consumption optimization in WSNs.

This unique text/reference provides a coherent and comprehensive overview of all aspects of video analysis of humans. Broad in coverage and accessible in style, the text presents original perspectives collected from preeminent researchers gathered from across the world. In addition to presenting state-of-the-art research, the book reviews the historical origins of the different existing methods, and predicts future trends and challenges. Features: with a Foreword by Professor Larry Davis; contains contributions from an international selection of leading authorities in the field; includes an extensive glossary; discusses the problems associated with detecting and tracking people through camera networks; examines topics related to determining the time-varying 3D pose of a person from video; investigates the representation and recognition of human and vehicular actions; reviews the most important applications of activity recognition, from biometrics and surveillance, to sports and driver assistance.

This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques.

Human Activity and Behavior Analysis relates to the field of vision and sensor-based human action or activity and behavior analysis and recognition. The book includes a series of methodologies, surveys, relevant datasets, challenging applications, ideas, and future prospects. The book discusses topics such as action recognition, action understanding, gait analysis, gesture recognition, behavior analysis, emotion and affective computing, and related areas. This volume focuses on relevant activities in three main subject areas: Healthcare and Emotion, Mental Health, and Nurse Care Records. The editors are experts in these arenas and the contributing authors are drawn from high-impact research groups around the world. This book will be of great interest to academics, students, and professionals working and researching in the field of human activity and behavior analysis.