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

  • Ahmed, Shahzad
  • Khan, Faheem
  • Ghaffar, Asim
  • Hussain, Farhan
  • Cho, Sung Ho
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47

초록

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.

키워드

impulse radar sensorgesture recognitionfinger countingdeep learning classifierconvolutional neural networkConvolutionDeep learningHuman computer interactionNeural networksPalmprint recognitionRadarRadar equipmentApplication areaConvolutional neural networkFinger countingHand-gesture recognitionImpulse radarsLearning classifiersOptimal locationsTouch-based interfaceGesture recognition
제목
Finger-Counting-Based Gesture Recognition within Cars Using Impulse Radar with Convolutional Neural Network
저자
Ahmed, ShahzadKhan, FaheemGhaffar, AsimHussain, FarhanCho, Sung Ho
DOI
10.3390/s19061429
발행일
2019-03
유형
Article
저널명
Sensors
19
6

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