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RF-based Pose Estimation

Detect human actions through walls and occlusions, and in poor lighting conditions. Taking radio frequency (RF) signals as input (e.g. Wifi), generating 3D human skeletons as an intermediate representation, and recognizing actions and interactions.

See e.g. RF-Pose from MIT for a good illustration of the approach http://rfpose.csail.mit.edu/

( Image credit: Making the Invisible Visible )

Papers

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Showing 1–16 of 16 papers

TitleStatusHype
Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical AggregationCode1
Can WiFi Estimate Person Pose?Code0
Person-in-WiFi: Fine-grained Person Perception using WiFiCode0
Light-Field for RF—0
Making the Invisible Visible: Action Recognition Through Walls and Occlusions—0
MDPose: Human Skeletal Motion Reconstruction Using WiFi Micro-Doppler Signatures—0
Milli-RIO: Ego-Motion Estimation with Millimetre-Wave Radar and Inertial Measurement Unit Sensor—0
Real Time 3D Indoor Human Image Capturing Based on FMCW Radar—0
RF-based 3D skeletons—0
RF-Based Fall Monitoring Using Convolutional Neural Networks—0
Segmented convolutional gated recurrent neural networks for human activity recognition in ultra-wideband radar—0
Through-Wall Human Pose Estimation Using Radio Signals—0
AI-Enhanced 3D RF Representation Using Low-Cost mmWave Radar—0
Through-Wall Object Recognition and Pose Estimation—0
A Survey on CSI-Based Human Behavior Recognition in Through-the-Wall Scenario—0
Enabling Noninvasive Physical Assault Monitoring in Smart School with Commercial Wi-Fi Devices—0
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