# mmSense: Detecting Concealed Weapons with a Miniature Radar Sensor

arXiv: https://arxiv.org/abs/2302.14625 · HTML: https://mlsanity.com/paper/2302.14625/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 12 references that are in the map.
- First posted on arXiv 28 Feb 2023.

## Builds on (most cited first, 2 of 2)

- [MmWave Radar and Vision Fusion for Object Detection in Autonomous Driving: A Review](https://mlsanity.com/paper/2108.03004/) (2021)
- [Millimeter-wave Foresight Sensing for Safety and Resilience in Autonomous Operations](https://mlsanity.com/paper/2203.12987/) (2022)

## Abstract (arXiv)

For widespread adoption, public security and surveillance systems must be accurate, portable, compact, and real-time, without impeding the privacy of the individuals being observed. Current systems broadly fall into two categories -- image-based which are accurate, but lack privacy, and RF signal-based, which preserve privacy but lack portability, compactness and accuracy. Our paper proposes mmSense, an end-to-end portable miniaturised real-time system that can accurately detect the presence of concealed metallic objects on persons in a discrete, privacy-preserving modality. mmSense features millimeter wave radar technology, provided by Google's Soli sensor for its data acquisition, and TransDope, our real-time neural network, capable of processing a single radar data frame in 19 ms. mmSense achieves high recognition rates on a diverse set of challenging scenes while running on standard laptop hardware, demonstrating a significant advancement towards creating portable, cost-effective real-time radar based surveillance systems.