G3R: Generating Rich and Fine-grained mmWave Radar Data from 2D Videos for Generalized Gesture Recognition

arXiv:2404.14934v1 Announce Type: cross
Abstract: Millimeter wave radar is gaining traction recently as a promising modality for enabling pervasive and privacy-preserving gesture recognition. However, the lack of rich and fine-grained radar datasets hinders progress in developing generalized deep learning models for gesture recognition across various user postures (e.g., standing, sitting), positions, and scenes. To remedy this, we resort to designing a software pipeline that exploits wealthy 2D videos to generate realistic radar data, but it needs to address the challenge …

abstract arxiv cs.cv cs.hc cs.mm data datasets deep learning enabling fine-grained generalized gesture recognition however millimeter wave privacy progress radar recognition type videos