Finger-Counting-Based Gesture Recognition within Cars Using Impulse Radar with Convolutional Neural Networkopen access
- Authors
- Ahmed, Shahzad; Khan, Faheem; Ghaffar, Asim; Hussain, Farhan; Cho, Sung Ho
- Issue Date
- Mar-2019
- Publisher
- MDPI
- Keywords
- impulse radar sensor; gesture recognition; finger counting; deep learning classifier; convolutional neural network
- Citation
- SENSORS, v.19, no.6
- Indexed
- SCIE
SCOPUS
- Journal Title
- SENSORS
- Volume
- 19
- Number
- 6
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/14994
- DOI
- 10.3390/s19061429
- ISSN
- 1424-8220
- Abstract
- 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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Collections - 서울 공과대학 > 서울 융합전자공학부 > 1. Journal Articles
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