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Multi-modal 3D Human Pose Estimation using mmWave, RGB-D, and Inertial Sensors
Sizhe An · Yin Li · Umit Ogras

Fri Dec 02 01:00 PM -- 02:00 PM (PST) @
Event URL: https://openreview.net/forum?id=6-SdB-dzXVm »

The ability to estimate 3D human body pose and movement, also known as human pose estimation~(HPE), enables many applications for home-based health monitoring, such as remote rehabilitation training. Several possible solutions have emerged using sensors ranging from RGB cameras, depth sensors, millimeter-Wave (mmWave) radars, and wearable inertial sensors. Despite previous efforts on datasets and benchmarks for HPE, few dataset exploits multiple modalities and focuses on home-based health monitoring. To bridge this gap, we present human pose estimation using multiple modalities with an in-house dataset. We perform extensive experiments and delineate the strength of each modality.

Author Information

Sizhe An (University of Wisconsin-Madison)
Yin Li (University of Wisconsin-Madison)
Umit Ogras (University of Wisconsin - Madison)

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