Nostril-Anchored Geometric ROI Projection for Contactless Forehead Skin Temperature Estimation Using Low-Resolution Thermal Imaging

(1) Background: Reliable forehead region-of-interest (ROI) localization remains challenging in low-resolution thermal imaging because limited spatial detail increases localization uncertainty. This study develops a lightweight nostril-anchored geometric ROI projection method for contactless forehead skin temperature estimation. (2) Methods: The forehead ROI was projected from the detected nostril bounding box using anthropometry-guided proportional geometry, followed by 95th-percentile (P95) spatial aggregation and exponential moving average (EMA) stabilization. Direct localization was evaluated against fixed-crop and MediaPipe Pose-based baselines using 120 annotated pilot frames across 0.5–1.5 m, followed by validation on 150 additional annotated frames from ten formal participants. A medical non-contact infrared forehead thermometer targeting the same central forehead region was used as a practical, rather than traceably calibrated, comparator. (3) Results: The proposed method outperformed the two localization baselines in the pilot evaluation. Formal-cohort validation achieved an overall IoU of 0.714, FIR of 0.870, and NCE of 0.091, with a 0.7% spatial-failure rate. Across 90 temperature measurements, the method achieved an MAE of 0.514 °C, RMSE of 0.614 °C, and mean bias of −0.187 °C, with 95% Bland–Altman limits of agreement from −1.340 °C to 0.966 °C. Real-time implementation achieved 24.12±1.43 FPS on a Jetson Orin Nano. (4) Conclusions: The proposed method provides a computationally efficient forehead ROI localization approach for low-resolution thermal imaging. Localization was strongest at 0.5 m and lower at farther distances; therefore, its scale adaptation should not be interpreted as distance-invariant performance. The temperature results represent agreement with the practical comparator rather than absolute clinical accuracy.

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Publication Details

Journal
Sensors
Published
2026-08-14
DOI
https://doi.org/10.3390/s26165147
Primary Topic
Infrared Thermography in Medicine
Type
article
Field-Weighted Citation Impact
0.00

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article

Nostril-Anchored Geometric ROI Projection for Contactless Forehead Skin Temperature Estimation Using Low-Resolution Thermal Imaging

Riska Analia, Anne Förster, Sheng Quan Xie, Zhiqiang Zhang
Sensors
Infrared Thermography in Medicine
article

Nostril-Anchored Geometric ROI Projection for Contactless Forehead Skin Temperature Estimation Using Low-Resolution Thermal Imaging

Riska Analia, Anne Förster, Sheng Quan Xie, Zhiqiang Zhang
article en

Abstract

(1) Background: Reliable forehead region-of-interest (ROI) localization remains challenging in low-resolution thermal imaging because limited spatial detail increases localization uncertainty. This study develops a lightweight nostril-anchored geometric ROI projection method for contactless forehead skin temperature estimation. (2) Methods: The forehead ROI was projected from the detected nostril bounding box using anthropometry-guided proportional geometry, followed by 95th-percentile (P95) spatial aggregation and exponential moving average (EMA) stabilization. Direct localization was evaluated against fixed-crop and MediaPipe Pose-based baselines using 120 annotated pilot frames across 0.5–1.5 m, followed by validation on 150 additional annotated frames from ten formal participants. A medical non-contact infrared forehead thermometer targeting the same central forehead region was used as a practical, rather than traceably calibrated, comparator. (3) Results: The proposed method outperformed the two localization baselines in the pilot evaluation. Formal-cohort validation achieved an overall IoU of 0.714, FIR of 0.870, and NCE of 0.091, with a 0.7% spatial-failure rate. Across 90 temperature measurements, the method achieved an MAE of 0.514 °C, RMSE of 0.614 °C, and mean bias of −0.187 °C, with 95% Bland–Altman limits of agreement from −1.340 °C to 0.966 °C. Real-time implementation achieved 24.12±1.43 FPS on a Jetson Orin Nano. (4) Conclusions: The proposed method provides a computationally efficient forehead ROI localization approach for low-resolution thermal imaging. Localization was strongest at 0.5 m and lower at farther distances; therefore, its scale adaptation should not be interpreted as distance-invariant performance. The temperature results represent agreement with the practical comparator rather than absolute clinical accuracy.

SensorsVol. 26(16)
University of Leeds (GB), Universitas Batam (ID), Politeknik Negeri Batam
Lembaga Pengelola Dana Pendidikan
Openalex Percentile: Top 10%
Infrared Thermography in Medicine
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