5 papers
IMU-HOI: A Symbiotic Framework for Coherent Human-Object Interaction and Motion Capture via Contact-Conscious Inertial Fusion
Lizhou Lin, Songpengcheng Xia, Zengyuan Lai +3
Capturing full-body human motion with object interactions is crucial for AR/VR and robotics applications, yet it remains challenging for conventional vision-based methods due to oc…
Suite-IN++: A FlexiWear BodyNet Integrating Global and Local Motion Features from Apple Suite for Robust Inertial Navigation
Lan Sun, Songpengcheng Xia, Jiarui Yang +1
The proliferation of wearable technology has established multi-device ecosystems comprising smartphones, smartwatches, and headphones as critical enablers for ubiquitous pedestrian…
RadarLLM: Empowering Large Language Models to Understand Human Motion from Millimeter-Wave Point Cloud Sequence
Zengyuan Lai, Jiarui Yang, Songpengcheng Xia +6
Millimeter-wave radar offers a privacy-preserving and environment-robust alternative to vision-based sensing, enabling human motion analysis in challenging conditions such as low l…
mmDEAR: mmWave Point Cloud Density Enhancement for Accurate Human Body Reconstruction
Jiarui Yang, Songpengcheng Xia, Zengyuan Lai +4
Millimeter-wave (mmWave) radar offers robust sensing capabilities in diverse environments, making it a highly promising solution for human body reconstruction due to its privacy-fr…
Suite-IN: Aggregating Motion Features from Apple Suite for Robust Inertial Navigation
Lan Sun, Songpengcheng Xia, Junyuan Deng +4
With the rapid development of wearable technology, devices like smartphones, smartwatches, and headphones equipped with IMUs have become essential for applications such as pedestri…