Statistical Hand Gesture Recognition System Using the Leap Motion Controller

Statistical Hand Gesture Recognition System Using the Leap Motion Controller
Author: Michael Dimartino
Publisher:
Total Pages: 44
Release: 2016
Genre:
ISBN:
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As technology continues to improve, hand gesture recognition as a form of humancomputer interaction is becoming more and more feasible. One such piece of technology, the Leap Motion Controller, provides 3D tracking data of the hands through an easy-to-use API. This thesis presents an application that uses Leap Motion tracking data to learn and recognize static and dynamic hand gestures. Gestures are recognized using statistical pattern recognition. Each gesture is defined by a set of features including fingertip positions, hand orientation, and movement. Given sufficient training data, the similarity between two gestures is measured by comparing each of their corresponding features. Two separate implementations are presented for dealing with the temporal aspect of dynamic gestures. Users are able to interact with the system using a convenient graphical user interface. The accuracy of the system was experimentally tested with the help of two separate test participants: one for the training phase and one for the recognition phase. All test gestures (both static and dynamic) were successfully recognized with minimal training data. In some cases, additional gestures were mistakenly recognized.

Intelligent Human Systems Integration 2021

Intelligent Human Systems Integration 2021
Author: Dario Russo
Publisher: Springer Nature
Total Pages: 911
Release: 2021-01-25
Genre: Technology & Engineering
ISBN: 3030680177
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This book presents cutting-edge research on innovative human systems integration and human–machine interaction, with an emphasis on artificial intelligence and automation, as well as computational modeling and simulation. It covers a wide range of applications in the area of design, construction and operation of products, systems and services. The book describes advanced methodologies and tools for evaluating and improving interface usability, new models, and case studies and best practices in virtual, augmented and mixed reality systems, with a special focus on dynamic environments. It also discusses various factors concerning the human user, hardware, and artificial intelligence software. Based on the proceedings of the 4th International Conference on Intelligent Human Systems Integration (IHSI 2021), held on February 22–24, 2021, the book also examines the forces that are currently shaping the nature of computing and cognitive systems, such as the need to reduce hardware costs; the importance of infusing intelligence and automation; the trend toward hardware miniaturization and optimization; the need for a better assimilation of computation in the environment; and social concerns regarding access to computers and systems for people with special needs. It offers a timely survey and a practice-oriented reference guide for policy- and decision-makers, human factors engineers, systems developers and users alike.

Advanced Methods and Applications for Neurointelligence

Advanced Methods and Applications for Neurointelligence
Author: Manning Wang
Publisher: Frontiers Media SA
Total Pages: 169
Release: 2024-05-31
Genre: Science
ISBN: 2832549861
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Neurointelligence techniques play a key role in building general artificial intelligence systems. Some researchers and engineers have tried to design novel bio-inspired algorithms and hardware by mimicking the working principles of biological nervous systems. Benefiting from the progress in representational learning, neuroscience, and computational hardware, bio-inspired research has greatly contributed to the development of neurointelligence. Currently, advanced bio-inspired methods have been widely applied in robotics, visual scene understanding, medical image analysis, human-machine interaction and so on. Moreover, neurointelligence covers interdisciplinary topics with neuroscience, robotics, artificial intelligence, cognitive science, machine learning, and pattern recognition. This research topic is intended to provide a better understanding of the opportunities, challenges, and promising future directions for neurointelligence.

Challenges and Applications for Hand Gesture Recognition

Challenges and Applications for Hand Gesture Recognition
Author: Kane, Lalit
Publisher: IGI Global
Total Pages: 249
Release: 2022-03-25
Genre: Computers
ISBN: 1799894363
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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.

Deep Learning in Personalized Healthcare and Decision Support

Deep Learning in Personalized Healthcare and Decision Support
Author: Harish Garg
Publisher: Elsevier
Total Pages: 402
Release: 2023-07-20
Genre: Computers
ISBN: 0443194149
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Deep Learning in Personalized Healthcare and Decision Support discusses the potential of deep learning technologies in the healthcare sector. The book covers the application of deep learning tools and techniques in diverse areas of healthcare, such as medical image classification, telemedicine, clinical decision support system, clinical trials, electronic health records, precision medication, Parkinson disease detection, genomics, and drug discovery. In addition, it discusses the use of DL for fraud detection and internet of things. This is a valuable resource for researchers, graduate students and healthcare professionals who are interested in learning more about deep learning applied to the healthcare sector. Although there is an increasing interest by clinicians and healthcare workers, they still lack enough knowledge to efficiently choose and make use of technologies currently available. This book fills that knowledge gap by bringing together experts from technology and clinical fields to cover the topics in depth. Discusses the application of deep learning in several areas of healthcare, including clinical trials, telemedicine and health records management Brings together experts in the intersection of deep learning, medicine, healthcare and programming to cover topics in an interdisciplinary way Uncovers the stakes and possibilities involved in realizing personalized healthcare services through efficient and effective deep learning technologies

Motion Tracking and Gesture Recognition

Motion Tracking and Gesture Recognition
Author: Carlos Travieso-Gonzalez
Publisher: BoD – Books on Demand
Total Pages: 175
Release: 2017-07-12
Genre: Computers
ISBN: 9535133772
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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.