Sensor Systems for Gesture Recognition
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 technolo...
Salvato in:
| Natura: | Online |
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| Lingua: | inglese |
| Pubblicazione: |
MDPI - Multidisciplinary Digital Publishing Institute
2024
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| Soggetti: | |
| Accesso online: | ONIX_20240108_9783036586946_144 |
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| _version_ | 1869518397056745472 |
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| collection | Directory of Open Access Books |
| 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. |
| format | Online |
| id | doab-20.500.12854ir-132485 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1324852024-03-30T12:51:23Z Sensor Systems for Gesture Recognition Saggio, Giovanni Benalcázar, Marco E. Gesture recognition Sensor systems Wearables Motion tracking Pattern recognition Gait analysis thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science 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. 2024-01-08T14:58:56Z 2024-01-08T14:58:56Z 2023 book ONIX_20240108_9783036586946_144 9783036586946 9783036586953 https://directory.doabooks.org/handle/20.500.12854/132485 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/8541 https://mdpi.com/books/pdfview/book/8541 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-8695-3 10.3390/books978-3-0365-8695-3 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036586946 9783036586953 338 open access |
| spellingShingle | Gesture recognition Sensor systems Wearables Motion tracking Pattern recognition Gait analysis thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science Sensor Systems for Gesture Recognition |
| title | Sensor Systems for Gesture Recognition |
| title_full | Sensor Systems for Gesture Recognition |
| title_fullStr | Sensor Systems for Gesture Recognition |
| title_full_unstemmed | Sensor Systems for Gesture Recognition |
| title_short | Sensor Systems for Gesture Recognition |
| title_sort | sensor systems for gesture recognition |
| topic | Gesture recognition Sensor systems Wearables Motion tracking Pattern recognition Gait analysis thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science |
| topic_facet | Gesture recognition Sensor systems Wearables Motion tracking Pattern recognition Gait analysis thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science |
| url | ONIX_20240108_9783036586946_144 |