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

• Published in: IEEE transactions on cybernetics Vol. 52; no. 10; pp. 10027 - 10040
• Main Authors: Roche, Jamie, De-Silva, Varuna, Hook, Joosep, Moencks, Mirco, Kondoz, Ahmet
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 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

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...