Contextual thermal face detection for fever mass screening

Siti Sofiah, Mohd Radzi and Kamarul Hawari, Ghazali and Sabira, Khatun (2017) Contextual thermal face detection for fever mass screening. Advanced Science Letters, 23 (11). pp. 11330-11334. ISSN 1936-6612. (Published)

[img]
Preview
Pdf
Contextual thermal face detection for fever mass screening.pdf

Download (660kB) | Preview

Abstract

In recent years, the global outbreak of severe acute respiratory syndrome detection and human tracking using infrared sensors get attention by many researchers. Machine vision plays an important role for successful conduction of above researchers. In most of the researches, focus is given on thermal spectrum, very less focus on the effectiveness of febrile mass detection and screening. For detection, usually the region of interest is the exposed area of head-to-shoulder. This is essential prior to measure the temperature of a febrile person by the thermal camera. Challenges to detect pedestrian in a crowd through thermal images include the image background and nature, quality of image in infrared spectrum as well as the real crowd situation in public area that cause occlusion. In this paper, a well-annotated pedestrian dataset is developed using thermal images taken during fever screening in Kuala Lumpur International Airport (KLIA). Then the statistical analysis on size and occlusion patterns in the streaming crowds has been performed. Finally, a local context detector is introduced, by taking into account the local context on head in thermal datasets for better detection performance. The performance proposed detector is evaluated on the developed thermal images dataset. Overall, it shows highest performance compared to existing pre-trained detectors.

Item Type: Article
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Crowd; Data set; Detection; Evaluation; Fever; HOG; Haar; KLIA; LBP; Mass screening; Thermal
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Institute of Postgraduate Studies
Depositing User: Mrs Norsaini Abdul Samat
Date Deposited: 04 Nov 2022 09:24
Last Modified: 04 Nov 2022 09:24
URI: http://umpir.ump.edu.my/id/eprint/28964
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item