FERT: Real-Time Facial Expression Recognition with Short-Range FMCW Radar

Sabri Mustafa Kahya, Muhammet Sami Yavuz, Eckehard Steinbach
11/18/2024
cs.CVcs.LGeess.SP

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Abstract

This study proposes a novel approach for real-time facial expression recognition utilizing short-range Frequency-Modulated Continuous-Wave (FMCW) radar equipped with one transmit (Tx), and three receive (Rx) antennas. The system leverages four distinct modalities simultaneously: Range-Doppler images (RDIs), micro range-Doppler Images (micro-RDIs), range azimuth images (RAIs), and range elevation images (REIs). Our innovative architecture integrates feature extractor blocks, intermediate feature extractor blocks, and a ResNet block to accurately classify facial expressions into smile, anger, neutral, and no-face classes. Our model achieves an average classification accuracy of 98.91% on the dataset collected using a 60 GHz short-range FMCW radar. The proposed solution operates in real-time in a person-independent manner, which shows the potential use of low-cost FMCW radars for effective facial expression recognition in various applications.

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Cite this paper

@article{kahya2024fert,
  title  = {FERT: Real-Time Facial Expression Recognition with Short-Range FMCW Radar},
  author = {Sabri Mustafa Kahya and Muhammet Sami Yavuz and Eckehard Steinbach},
  year   = {2024},
  eprint = {2411.11619},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2411.11619v1}
}

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