Gesture Recognition Method Based on Millimeter Wave Radar
LIU Guoyong
MA Lubiao
HUANG Tingpei
Abstract：Millimeter wave radar gesture recognition,as a new type of contactless human-computer interaction(HCI),has a wide range of application prospects in the fields of smart driving,smart home,and physical games.Although the existing work has achieved excellent recognition accuracy in a laboratory environment,it is still limited in practical applications due to the intensive data collection effort required,the poor robustness of the system in the new environment,and the recognition scheme based on the offline form.To address the above issues,in this paper,range-doppler images of eight common hand gestures are collected by using the IWR1843 BOOST millimeter wave radar sensor,on the basis of which a gesture dataset is built.The problem of poor cross-envi-ronment recognition performance of the system is solved by using the proposed interference elimination algorithm and data enhance-ment algorithm.In addition,the online segmentation performance of the system is enhanced by the gesture sample segmentation al-gorithm based on the detection window and recognition window.The experimental results show that the system achieves 98.26%rec-ognition accuracy on the dataset with an average inference delay of 24 ms.Compared with the conventional sliding window-based gesture recognition system,it features low inference delay and high recognition accuracy.
Keywords：gesture recognitionmillimeter wave radarhuman-computer interactiondata augmentationdeep learning
Publication Date：2025-12-20
Online Publishing Date：2026-03-09(First online date of this platform, not the publication date of the document)
Pages：6( 3534-3539 )