On the Use of Low-Cost Radars and Machine Learning for In-Vehicle Passenger Detection

  • Hajar Abedi
  • Shenghang Luo
  • Steven Ding
  • Clara Magnier
  • Michael Bacani
  • George Shaker

Abstract

In this paper, we use a low-cost low-power mm-wave frequency
modulated continuous wave (FMCW) radar for in-vehicle occupant
monitoring. We propose an algorithm to identify occupied seats. In-
stead of using a high-resolution radar which increases the cost and
area, we integrate machine learning algorithms with the results of
covariance-based angle of arrival estimation capon beamformer.

Published
2020-01-02
How to Cite
Abedi, H., Luo, S., Ding, S., Magnier, C., Bacani, M., & Shaker, G. (2020). On the Use of Low-Cost Radars and Machine Learning for In-Vehicle Passenger Detection. Journal of Computational Vision and Imaging Systems, 5(1), 2. Retrieved from https://openjournals.uwaterloo.ca/index.php/vsl/article/view/1653