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Author: Giovanni Saggio
Publisher: Mdpi AG
ISBN: 9783036586946
Category : Computers
Languages : en
Pages : 0
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Book Description
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: Giovanni Saggio
Publisher: Mdpi AG
ISBN: 9783036586946
Category : Computers
Languages : en
Pages : 0
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Book Description
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: Giovanni Saggio
Publisher:
ISBN: 9783036585468
Category :
Languages : en
Pages : 0
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Book Description
This second Special Issue was compiled because of the interest demonstrated by the great success of the first Special Issue devoted to "Sensor Systems for Gesture Recognition".We believe this reprint acts as a meaningful window towards "Gesture Recognition" and the related sensors allowing the gathering of necessary data.
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: 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: Carlos Travieso-Gonzalez
Publisher: BoD – Books on Demand
ISBN: 9535133772
Category : Computers
Languages : en
Pages : 175
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Book Description
Nowadays, the technological advances allow developing many applications on different fields. In this book Motion Tracking and Gesture Recognition, two important fields are shown. Motion tracking is observed by a hand-tracking system for surgical training, an approach based on detection of dangerous situation by the prediction of moving objects, an approach based on human motion detection results and preliminary environmental information to build a long-term context model to describe and predict human activities, and a review about multispeaker tracking on different modalities. On the other hand, gesture recognition is shown by a gait recognition approach using Kinect sensor, a study of different methodologies for studying gesture recognition on depth images, and a review about human action recognition and the details about a particular technique based on a sensor of visible range and with depth information.
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: Qiguang Miao
Publisher: Elsevier
ISBN: 0443289603
Category : Computers
Languages : en
Pages : 225
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Book Description
Gesture Recognition: Theory and Applications covers this important topic in computer science and language technology that has a goal of interpreting human gestures via mathematical algorithms. The book begins by examining the computer vision-based gesture recognition method, focusing on the theory and related research results of various recent gesture recognition technologies. The book takes the evolutions of gesture recognition technology as a clue, systematically introducing gesture recognition methods based on handcrafted features, convolutional neural networks, recurrent neural networks, multimodal data fusion, and visual attention mechanisms. Three gesture recognition-based HCI (Human Computer Interaction) practical cases are introduced. Finally, the book looks at emerging research trends and application. Focuses on the theory and application of gesture recognition, providing a systematic introduction to commonly used datasets in the field as well as algorithms based on handcrafted features, convolutional neural networks, multimodal fusion, and attention mechanisms Introduces the practical applications of gesture recognition in real-world scenarios, enabling readers to enhance their practical application skills while learning about relevant technologies Demonstrates four main categories of gesture recognition methods and analyzes their associated challenges
Author: Stephen Hailes
Publisher: Springer Science & Business Media
ISBN: 3642115276
Category : Computers
Languages : en
Pages : 298
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Book Description
The First International ICST Conference on Sensor Systems and Software (S-cube 2009) was held during 7–8 September in Pisa, Italy. This new international conference was dedicated to addressing the research challenges facing system dev- opment and software support for systems based on wireless sensor networks (WSNs) that have the potential to impact society in many ways. Currently, wireless sensor networks introduce innovative and interesting application scenarios that may support a large amount of different applications including environmental monitoring, disaster prevention, building automation, object tracking, nuclear reactor control, fire det- tion, agriculture, healthcare, and traffic monitoring. The widespread acceptance of these new services can be improved by the definition of frameworks and architectures that have the potential to radically simplify software development for wireless sensor network-based applications. The aim of these new architectures is to support flexible, scalable programming of applications based on adaptive middleware. As a con- quence, WSNs require novel programming paradigms and technologies. Moreover, the design of new complex systems, characterized by the interaction of different and heterogeneous resources, will allow the development of innovative applications that meet high-performance goals. Hence, WSNs require contributions from many fields such as embedded systems, distributed systems, data management, system security and applications. The conference places emphasis on layers well above the traditional MAC and routing and transport layer protocols.
Author: Steven Daniel Lovell
Publisher:
ISBN:
Category :
Languages : en
Pages : 103
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Book Description
This thesis describes the design and implementation of a wireless 6 degree-of-freedom inertial sensor system to be used for multiple-user, real-time gesture recognition and coordinated activity detection. Analysis is presented that shows that the data streams captured can be readily processed to detect gestures and coordinated activity. Finally, some pertinent research that can be pursued with these nodes in the areas of biomotion analysis and interactive entertainment are introduced.
Author: Charlotte Meroni
Publisher:
ISBN:
Category :
Languages : it
Pages :
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Book Description
