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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

Showing 1–10 of 16 papers

TitleStatusHype
Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical AggregationCode1
MDPose: Human Skeletal Motion Reconstruction Using WiFi Micro-Doppler Signatures—0
Making the Invisible Visible: Action Recognition Through Walls and Occlusions—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
A Survey on CSI-Based Human Behavior Recognition in Through-the-Wall Scenario—0
Through-Wall Object Recognition and Pose Estimation—0
Segmented convolutional gated recurrent neural networks for human activity recognition in ultra-wideband radar—0
Enabling Noninvasive Physical Assault Monitoring in Smart School with Commercial Wi-Fi Devices—0
Person-in-WiFi: Fine-grained Person Perception using WiFiCode0
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