This study evaluates the feasibility of using two affordable thermal cameras (UNI-T UTi260M and UTi260T), which are not designed as automotive sensors, for observing pedestrians and warm objects during night-time driving under low-illumination conditions. The experimental setup includes mounting the camera on the vehicle body (e.g., side mirror area/roof), recording road scenes in urban and rural environments, and selecting representative frames for qualitative and quantitative analysis. The study assesses: (i) observable pedestrian detectability in unlit road sections and under oncoming headlight glare, where visible cameras often lose contrast; (ii) the influence of low ambient temperature and strong cold wind on image appearance (including “whitening”/contrast shifts); and (iii) workflow differences, where UTi260M relies on a smartphone application for streaming/recording, while UTi260T supports PC-based image analysis and temperature-profile visualization. In addition, a calibration-based geometric method is proposed for approximate pedestrian distance estimation from single frames using silhouette pixel height and a regression model based on 1/hpx, valid for a specific mounting configuration and a known subject height. Results indicate that both cameras can highlight warm objects relative to the background and support visual pedestrian identification at low illumination, including in the presence of oncoming headlights, with UTi260M showing more stable behavior in parts of the tests. This work is a feasibility study and does not claim Advanced Driver Assist Systems (ADAS) functionality; it outlines limitations, repeatability considerations, and a minimal set of metrics and procedures for future extension. All quantitative indicators derived from exported frames are explicitly treated as image-level proxy metrics, not as physical sensor characteristics.
Stoyanov et al. (2026) studied this question.