# Efficient Convolutional Neural Network for FMCW Radar Based Hand Gesture Recognition

arXiv: https://arxiv.org/abs/1908.10560 · HTML: https://mlsanity.com/paper/1908.10560/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Aug 2019.

## Built on by (most cited first, 2 of 2)

- [OCHID-Fi: Occlusion-Robust Hand Pose Estimation in 3D via RF-Vision](https://mlsanity.com/paper/2308.10146/) (2023)
- [Hand gesture recognition using 802.11ad mmWave sensor in the mobile device](https://mlsanity.com/paper/2211.07090/) (2022)

## Abstract (arXiv)

FMCW radar could detect object's range, speed and Angleof-Arrival, advantages are robust to bad weather, good range resolution, and good speed resolution. In this paper, we consider the FMCW radar as a novel interacting interface on laptop. We merge sequences of object's range, speed, azimuth information into single input, then feed to a convolution neural network to learn spatial and temporal patterns. Our model achieved 96% accuracy on test set and real-time test.