Reprint

Sensor Systems for Gesture Recognition II

Edited by
August 2023
254 pages
  • ISBN978-3-0365-8547-5 (Hardback)
  • ISBN978-3-0365-8546-8 (PDF)

This book is a reprint of the Special Issue Sensor Systems for Gesture Recognition II that was published in

Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Summary

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.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
abnormal gait behavior; OpenPose; machine learning; XGBoost; random forest; horse locomotion; training effect; inertial measurement units; sports technology; football; motion analysis; IMU; trajectory reconstruction; human-computer interactive; data glove; virtual hand; emotion driven; test; visual tracking; Siamese tracker; tracking drift; background clutter; deep learning; surgical skills assessment; machine learning; computer vision; surgical education; biomedical engineering; multi-modal; human activity recognition; markerless; RGB-D; general movements; infant movement analysis; movement disorders; surface electromyography; forearm amputee; hand posture; visual feedback training; pattern recognition; artificial neural network; hand gesture recognition; electromyography; inertial measurement unit; reinforcement learning; deep Q-network; extreme learning machine; force myography; grasshopper optimization algorithm; k-tournament selection; frequency emphasis; ensemble learning; deep learning; sign language recognition; gloss prediction; transformer; pose-based approach; pose estimation; deep learning; emotion judgment system; adaptive interactive game; set of optimal signal features; sensor; MARG; MIMU; orientation estimation; sensor fusion algorithm; dataset; orientation algorithm benchmarking