Abstract

Modern cars continue to offer more and more functionalities due to which they need a growing number of commands. As the driver tries to monitor the road and the graphic user interface simultaneously, his/her overall efficiency is reduced. In order to reduce the visual attention necessary for monitoring, a gesture-based user interface is very important. In this paper, gesture recognition for a vehicle through impulse radio ultra-wideband (IR-UWB) radar is discussed. The gestures can be used to control different electronic devices inside a vehicle. The gestures are based on human hand and finger motion. We have implemented a real-time version using only one radar sensor. Studies on gesture recognition using IR-UWB radar have rarely been carried out, and some studies are merely simple methods using the magnitude of the reflected signal or those whose performance deteriorates largely due to changes in distance or direction. In this study, we propose a new hand-based gesture recognition algorithm that works robustly against changes in distance or direction while responding only to defined gestures by ignoring meaningless motions. We used three independent features, i.e., variance of the probability density function (pdf) of the magnitude histogram, time of arrival (TOA) variation and the frequency of the reflected signal, to classify the gestures. A data fitting method is included to differentiate between gesture signals and unintended hand or body motions. We have used the clustering technique for the classification of the gestures. Moreover, the distance information is used as an additional input parameter to the clustering algorithm, such that the recognition technique will not be vulnerable to distance change. The hand-based gesture recognition proposed in this paper would be a key technology of future automobile user interfaces.

Highlights

  • Hand-based gesture recognition is one of the hottest research fields, since it is of great significance in designing artificially intelligent human computer interfaces

  • We have presented a robust algorithm for hand-based gesture recognition using an impulse radio ultra-wideband (IR-UWB)

  • We have presented a robust algorithm for gesture recognition

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Summary

Introduction

Hand-based gesture recognition is one of the hottest research fields, since it is of great significance in designing artificially intelligent human computer interfaces. Ren Nan et al [24] have presented an algorithm for big gesture recognition through IR-UWB radar, but the gestures detected in that work were based on the position difference of the hand and may not be useful in practical applications. The main problem noted in the past radar-based gesture recognition algorithms was that they were vulnerable to distance and orientation; and the feature extraction through machine learning caused the overfitting problem in some cases, which made them error prone. To overcome these problems, we have presented a robust algorithm for hand-based gesture recognition using an IR-UWB radar sensor in this paper.

Process
The gesture
Feature Extraction and Classification
Gesture
Section 2.2.3.
Time of Arrival Variance
Frequency
Finding
Gestures
11. K-means
Experimental
14. Gesture
The Detection of Only Intended Gestures’ Result
Clustering Classification Results
Conclusions

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