Touch-Point Detection Using Thermal Video With Applications to Prevent Indirect Virus Spread.
IEEE J Transl Eng Health Med
; 9: 4900711, 2021.
Article
in English
| MEDLINE | ID: covidwho-1411484
ABSTRACT
Viral and bacterial pathogens can be transmitted through direct contact with contaminated surfaces. Efficient decontamination of contaminated surfaces could lead to decreased disease transmission, if optimized methods for detecting contaminated surfaces can be developed. Here we describe such a method whereby thermal tracking technology is utilized to detect thermal signatures incurred by surfaces through direct contact. This is applicable in public places to assist with targeted sanitation and cleaning efforts to potentially reduce chance of disease transmission. In this study, we refer to the touched region of the surface as a "touch-point" and examine how the touch-point regions can be automatically localized with a computer vision pipeline of a thermal image sequence. The pipeline mainly comprises two components a single-frame and a multi-frame analysis. The single-frame analysis consists of a Background subtraction method for image pre-processing and a U-net deep learning model for segmenting the touch-point regions. The multi-frame analysis performs a summation of the outputs from the single-frame analysis and creates a cumulative map of touch-points. Results show that the touch-point detection pipeline can achieve 75.0% precision and 81.5% F1-score for the testing experiments of predicting the touch-point regions. This preliminary study shows potential applications of preventing indirect pathogen spread in public spaces and improving the efficiency of cleaning sanitation.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Viruses
/
Touch Perception
Type of study:
Prognostic study
Language:
English
Journal:
IEEE J Transl Eng Health Med
Year:
2021
Document Type:
Article
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