UWB Based Static Gesture Classification

arXiv:2310.15036v2 Announce Type: replace
Abstract: Our paper presents a robust framework for UWB-based static gesture recognition, leveraging proprietary UWB radar sensor technology. Extensive data collection efforts were undertaken to compile datasets containing five commonly used gestures. Our approach involves a comprehensive data pre-processing pipeline that encompasses outlier handling, aspect ratio-preserving resizing, and false-color image transformation. Both CNN and MobileNet models were trained on the processed images. Remarkably, our best-performing model achieved an accuracy of 96.78%. Additionally, we developed a user-friendly …

abstract arxiv classification collection color cs.ai cs.cv data data collection datasets false five framework gesture recognition gestures image outlier paper pipeline pre-processing processing proprietary radar recognition robust sensor technology transformation type