Finger-Counting-Based Gesture Recognition within Cars Using Impulse Radar with Convolutional Neural Network

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ID: 111556
2019
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Аннотация
The diversion of a driver’s attention from driving can be catastrophic. Given that conventional button- and touch-based interfaces may distract the driver, developing novel distraction-free interfaces for the various devices present in cars has becomes necessary. Hand gesture recognition may provide an alternative interface inside cars. Given that cars are the targeted application area, we determined the optimal location for the radar sensor, so that the signal reflected from the driver’s hand during gesturing is unaffected by interference from the motion of the driver’s body or other motions within the car. We implemented a Convolutional Neural Network-based technique to recognize the finger-counting-based hand gestures using an Impulse Radio (IR) radar sensor. The accuracy of the proposed method was sufficiently high for real-world applications.
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ahmed2019sensorsfinger-counting-based Используйте этот ключ для автоцитирования в рукописи при использовании SciMatic Manuscript Manager или Thesis Manager
Авторы Shahzad Ahmed;Faheem Khan;Asim Ghaffar;Farhan Hussain;Sung Ho Cho;Ahmed, Shahzad;Khan, Faheem;Ghaffar, Asim;Hussain, Farhan;Cho, Sung Ho;
Журнал sensors
Год 2019
DOI
10.3390/s19061429
URL
https://www.mdpi.com/1424-8220/19/6/1429/htm
Ключевые слова
Convolutional neural network finger counting gesture recognition impulse radar sensor deep learning classifier

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