A Multimodal Data Processing System for LiDAR-Based Human Activity Recognition

Increasingly, the task of detecting and recognizing the actions of a human has been delegated to some form of neural network processing camera or wearable sensor data. Due to the degree to which the camera can be affected by lighting and wearable sensors scantiness, neither one modality can capture...

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Veröffentlicht in:	IEEE transactions on cybernetics Jg. 52; H. 10; S. 10027 - 10040
Hauptverfasser:	Roche, Jamie, De-Silva, Varuna, Hook, Joosep, Moencks, Mirco, Kondoz, Ahmet
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.10.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Activity recognition Artificial neural networks Cameras Convolutional neural network Data processing Decision making faster RCNN Fisher vector Human activity recognition human activity recognition (HAR) Indoor environments Laser radar Lidar Machine learning Micromechanical devices multimodal machine learning (ML) Multisensor fusion Neural networks Sensors Three-dimensional displays Urban areas Wearable sensors Wearable technology
ISSN:	2168-2267, 2168-2275, 2168-2275
Online-Zugang:	Volltext
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