Tarnkappe.infoJan 19, 2023
📬 WLAN Router erlauben präzise Beobachtung von Personen
#Datenschutz #CarnegieMellonUniversity #DensePose #privatsphäre #Tracking #Überwachung #Überwachungskamera #WiFiSignal #WLANRouter https://tarnkappe.info/artikel/datenschutz/wlan-router-erlauben-praezise-beobachtung-von-personen-263324.html
WLAN Router erlauben präzise Beobachtung von Personen

WiFi-Signale gängiger WLAN-Router lassen sich inzwischen für das Tracking menschlicher Körper nutzen. Und das sogar durch Wände hindurch.

Tarnkappe.info
Luke Switzer 🅅Jan 18, 2023

Pose Detection via WiFi

"comparable performance to image-based approaches, by utilizing WiFi signals as the only input"

I first saw this in a defcon talk about radar imaging with a $35 SDR; Imagine what a real budget and hardware could do…

Until they share some code, I optimistically call bs.

#wifi #opsec #privacy #densepose

https://arxiv.org/abs/2301.00250

DensePose From WiFi

Advances in computer vision and machine learning techniques have led to significant development in 2D and 3D human pose estimation from RGB cameras, LiDAR, and radars. However, human pose estimation from images is adversely affected by occlusion and lighting, which are common in many scenarios of interest. Radar and LiDAR technologies, on the other hand, need specialized hardware that is expensive and power-intensive. Furthermore, placing these sensors in non-public areas raises significant privacy concerns. To address these limitations, recent research has explored the use of WiFi antennas (1D sensors) for body segmentation and key-point body detection. This paper further expands on the use of the WiFi signal in combination with deep learning architectures, commonly used in computer vision, to estimate dense human pose correspondence. We developed a deep neural network that maps the phase and amplitude of WiFi signals to UV coordinates within 24 human regions. The results of the study reveal that our model can estimate the dense pose of multiple subjects, with comparable performance to image-based approaches, by utilizing WiFi signals as the only input. This paves the way for low-cost, broadly accessible, and privacy-preserving algorithms for human sensing.

arXiv.org
David RossJun 18, 2018

Facebook #OpenSource|s (CC-AT-NC) #AI for images to 3D models.

#physiology #technique #training #analysis #DensePose

https://research.fb.com/facebook-open-sources-densepose/

Facebook open sources DensePose

Today, Facebook AI Research (FAIR) open sourced DensePose, our real-time approach for mapping all human pixels of 2D RGB images to a 3D surface-based model of the body. [caption id="attachment_8829" align="alignnone" width="984"] Left: Input, Middle: correspondence by DensePose-RCNN, Right: Partitioning and UV parameterization of the human body.[/caption] Recent research in human understanding aims primarily at…

Facebook Research