Inertial Measurement Unit Based Multi User Gesture Recognition PDF Download
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Author: Stephan Tietz
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Stephan Tietz
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Ari Yosef Benbasat
Publisher:
ISBN:
Category :
Languages : en
Pages : 135
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Author: Sergio Escalera
Publisher: Springer
ISBN: 3319570218
Category : Computers
Languages : en
Pages : 583
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Book Description
This book presents a selection of chapters, written by leading international researchers, related to the automatic analysis of gestures from still images and multi-modal RGB-Depth image sequences. It offers a comprehensive review of vision-based approaches for supervised gesture recognition methods that have been validated by various challenges. Several aspects of gesture recognition are reviewed, including data acquisition from different sources, feature extraction, learning, and recognition of gestures.
Author: Chaithanya Kumar Mummadi
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Giovanni Saggio
Publisher: Mdpi AG
ISBN: 9783036586946
Category : Computers
Languages : en
Pages : 0
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Gesture recognition (GR) aims to interpret human gestures, having an impact on a number of different application fields. This Special Issue is devoted to describing and examining up-to-date technologies to measure gestures, algorithms to interpret data, and applications related to GR. These technologies involve camera-based systems (e.g., ground truth system, GTS; Azura Kinect), wearable sensors (e.g., inertial measurement units, IMUs; micro electro-mechanical systems, MEMS; angular displacement sensors, ADS; resistive flex sensors, RFSs), electromagnetic field measurements (e.g., leap motion sensor), acoustic-based inputs (e.g., microphone, stethoscope), radar systems (e.g., continuous wave), and tactile sensors (e.g., pressure sensitive transistors). Data interpretations are detailed by means of classifiers (e.g., neural networks, NN; convolutional neural network, CNN; hidden Markov models, HMM; and k-nearest neighbors, kNN). The applications are for medical purposes (e.g., to provide physiotherapy solutions, to assess Parkinson's disease, and to electrocardiogram detection), for social inclusion (e.g., sign language recognition: British, American, and Italian ones), for sport activity scoring (e.g., taekwondo), for machine interaction (e.g., to control a holographic display), and for safety purposes (e.g., to drowsiness recognition). This Special Issue is addressed to all the researchers, professionals, and designers interested in GR and to all the users driven by curiosity and passion. The Guest Editors would like to acknowledge and express their gratitude to all of the authors involved.
Author: Samee U. Khan
Publisher: Springer
ISBN: 3319582801
Category : Computers
Languages : en
Pages : 630
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Book Description
This volume offers readers various perspectives and visions for cutting-edge research in ubiquitous healthcare. The topics emphasize large-scale architectures and high performance solutions for smart healthcare, healthcare monitoring using large-scale computing techniques, Internet of Things (IoT) and big data analytics for healthcare, Fog Computing, mobile health, large-scale medical data mining, advanced machine learning methods for mining multidimensional sensor data, smart homes, and resource allocation methods for the BANs. The book contains high quality chapters contributed by leading international researchers working in domains, such as e-Health, pervasive and context-aware computing, cloud, grid, cluster, and big-data computing. We are optimistic that the topics included in this book will provide a multidisciplinary research platform to the researchers, practitioners, and students from biomedical engineering, health informatics, computer science, and computer engineering.
Author: Xiaoliang Zhang
Publisher:
ISBN:
Category :
Languages : en
Pages : 69
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Book Description
Internet of wearable things (IoWT) has been used to exchange the information with other devices in recent years, regarding to provide body health information and make the wearables as a biomarker, many researchers such as scientists in the academia or engineers in the industry are trying to design a more reliable and smarter system in the fields of IoWT. This thesis described a novel upper limbs (hand and arm) motion detection system which used cooperative wearable sensing network consists of wearable armband and smart glove made by customizable pressure sensor arrays to detect personal dynamic hand gestures. The strength of such "cooperative wearable sensing network" is to reduce false positive with multi-sensors information fusion. A deep learning technique "Long Short-Term Memory" algorithm had been computed to build an effective model to classify hand gestures by training and testing the collected IMU (Inertial Measurement Unit), Electromyography (EMG), finger and palm's pressure data. In the experiments, this IoWT system was evaluated in common hand gesture recognition and specific scenario in smart health: smoking cessation study. Wearable sensors have the potential to improve current approaches by providing personalized feedback and objective verification of smoking status. This thesis combined the proposed IoWT system in hand gesture recognition with an Android software application to monitor smoking in real-time by detecting smoking and non-smoking dynamic hand gestures in daily life, such as "answering the phone", "drinking", "writing", etc. Findings have implications for using cooperative sensing technology in HGR fields and tobacco cessation treatment delivery and assessment of smoking status. This thesis describes wearable sensor systems design, Android things framework to establish a cooperative wearable sensing network, and streaming sensor data analysis through deep learning. A controlled smoking cessation pilot study was used as a case study to evaluate the design consideration and system performance of the developed IoWT system.
Author: J. K. Mandal
Publisher: Springer
ISBN: 8132222474
Category : Technology & Engineering
Languages : en
Pages : 858
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Book Description
The second international conference on INformation Systems Design and Intelligent Applications (INDIA – 2015) held in Kalyani, India during January 8-9, 2015. The book covers all aspects of information system design, computer science and technology, general sciences, and educational research. Upon a double blind review process, a number of high quality papers are selected and collected in the book, which is composed of two different volumes, and covers a variety of topics, including natural language processing, artificial intelligence, security and privacy, communications, wireless and sensor networks, microelectronics, circuit and systems, machine learning, soft computing, mobile computing and applications, cloud computing, software engineering, graphics and image processing, rural engineering, e-commerce, e-governance, business computing, molecular computing, nano computing, chemical computing, intelligent computing for GIS and remote sensing, bio-informatics and bio-computing. These fields are not only limited to computer researchers but also include mathematics, chemistry, biology, bio-chemistry, engineering, statistics, and all others in which computer techniques may assist.
Author: Kane, Lalit
Publisher: IGI Global
ISBN: 1799894363
Category : Computers
Languages : en
Pages : 249
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Book Description
Due to the rise of new applications in electronic appliances and pervasive devices, automated hand gesture recognition (HGR) has become an area of increasing interest. HGR developments have come a long way from the traditional sign language recognition (SLR) systems to depth and wearable sensor-based electronic devices. Where the former are more laboratory-oriented frameworks, the latter are comparatively realistic and practical systems. Based on various gestural traits, such as hand postures, gesture recognition takes different forms. Consequently, different interpretations can be associated with gestures in various application contexts. A considerable amount of research is still needed to introduce more practical gesture recognition systems and associated algorithms. Challenges and Applications for Hand Gesture Recognition highlights the state-of-the-art practices of HGR research and discusses key areas such as challenges, opportunities, and future directions. Covering a range of topics such as wearable sensors and hand kinematics, this critical reference source is ideal for researchers, academicians, scholars, industry professionals, engineers, instructors, and students.
Author: Ajith Abraham
Publisher: Springer Nature
ISBN: 3031275241
Category : Technology & Engineering
Languages : en
Pages : 931
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Book Description
This book highlights the recent research on soft computing, pattern recognition, nature-inspired computing, and their various practical applications. It presents 69 selected papers from the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2022) and 19 papers from the 14th World Congress on Nature and Biologically Inspired Computing (NaBIC 2022), which was held online, from December 14 to 16, 2022. A premier conference in the field of soft computing, artificial intelligence, and machine learning applications, SoCPaR-NaBIC 2022 brought together researchers, engineers, and practitioners whose work involves intelligent systems, network security, and their applications in industry. Including contributions by authors from over 25 countries, the book offers a valuable reference guide for all researchers, students, and practitioners in the fields of computer science and engineering.
