infrared sensors; human activity recognition; e-healthcare
Can we perceive the three-dimensional posture of the whole human body solely from extremely low-resolution thermal images (e.g., $8\times8$-pixels)?
This paper investigates the possibility of this challenging task.
Thermal images capture only the intensity of radiation, making them less likely to contain personal information such as facial or clothing features.
Thermal sensors are commonly integrated into daily-use appliances, such as air conditioners, automatic doors, and elevators.
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Coventry-2018 is a human activity recognition dataset captured by three Panasonic® Grid-EYE (AMG8833) infrared sensors in March 2018. The Grid-EYE sensors represent a 60 field of view scene by an 8 × 8 array named frame. The data streams are synchronized to 10 frames per second and saved as *.csv recordings using the LabVIEW® software. Two layouts are considered in this dataset with different geometry sizes: 1) small layout; and 2) large layout.
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