Journal article
CROMOSim: A Deep Learning-Based Cross-Modality Inertial Measurement Simulator
Abstract
With the prevalence of wearable devices, inertial measurement unit (IMU) data has been utilized in monitoring and assessing human mobility such as human activity recognition (HAR) and human pose estimation (HPE). Training deep neural network (DNN) models for these tasks require a large amount of labelled data, which are hard to acquire in uncontrolled environments. To mitigate the data scarcity problem, we design CROMOSim, a cross-modality …
Authors
Hao Y; Lou X; Wang B; Zheng R
Journal
IEEE Transactions on Mobile Computing, Vol. 23, No. 1, pp. 302–312
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
DOI
10.1109/tmc.2022.3230370
ISSN
1536-1233