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Fine-Grained and Real-Time Gesture Recognition by Using IMU Sensors
- Source :
- IEEE Transactions on Mobile Computing. 22:2177-2189
- Publication Year :
- 2023
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2023.
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Abstract
- Gesture recognition by using Inertial Measurement Unit (IMU) sensors plays an important role in various Internet of Things (IOT) applications, e.g., smart home, intelligent medical system and so on. Traditional technologies usually utilize machine learning algorithms to train different gestures during the offline phase, then recognize the gesture during the online phase. However, such technologies cannot recognize these gestures without prior training. Even for the same gesture, with different gesture amplitude may result in unsuccessful recognition. Also if we change the person to perform the same gesture, the algorithms fails. In order to overcome these drawbacks, we propose an approach, which will be able to track the human body motion in realtime and also recognize complicated gestures. It utilizes the accelerometer information and proposes comprehensive localization algorithms for each deployed sensor attached on the human body. Then, it takes the correlation and limitation among body parts into account to recognize the gesture. Our experiments results show that, the successful recognition rate of our algorithm is 100%. Furthermore, any part of the human body can be well tracked, the tracking accuracy can reach 0.06m.
- Subjects :
- Computer Networks and Communications
business.industry
Computer science
Human body
Tracking (particle physics)
Accelerometer
Motion (physics)
Home automation
Inertial measurement unit
Gesture recognition
Computer vision
Artificial intelligence
Electrical and Electronic Engineering
business
Software
Gesture
Subjects
Details
- ISSN :
- 21619875 and 15361233
- Volume :
- 22
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Mobile Computing
- Accession number :
- edsair.doi...........c6e0548dfc4c0b7dd198f40cd2393480