Oct. 11, 2022, 1:17 a.m. | Yadong Li, Dongheng Zhang, Jinbo Chen, Jinwei Wan, Dong Zhang, Yang Hu, Qibin Sun, Yan Chen

cs.CV updates on arXiv.org arxiv.org

Human gesture recognition using millimeter-wave (mmWave) signals provides
attractive applications including smart home and in-car interfaces. While
existing works achieve promising performance under controlled settings,
practical applications are still limited due to the need of intensive data
collection, extra training efforts when adapting to new domains, and poor
performance for real-time recognition. In this paper, we propose DI-Gesture, a
domain-independent and real-time mmWave gesture recognition system.
Specifically, we first derive signal variations corresponding to human gestures
with spatial-temporal processing. To …

arxiv gesture recognition independent real-time signal

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Software Engineer, Data Tools - Full Stack

@ DoorDash | Pune, India

Senior Data Analyst

@ Artsy | New York City