Continuous Human Activity Classification with Radar Point Clouds and Point Transformer Networks

Due to numerous benefits, radar is considered as an important sensor for human activity classification.The problem of classifying continuous sequences of activities of unconstrained duration has been studied in this work.To tackle this challenge, a radar data processing method utilizing point transformer networks has been proposed.The method has been experimentally verified on a dataset of human activities, and experiments have been performed to determine its optimal implementation.Promising preliminary results on a 9-class dataset show test accuracy and macro F-1 scores in the range of 83% and 73% respectively.