Segment-based region of interest generation for pedestrian detection in far-infrared images

• We utilize the low-frequency characteristics of FIR images for ROI generation.
• We generate ROIs based on combining image segments instead of using the intensity threshold.
• It generates a small number of ROIs at an acceptable miss rate.
• We introduce miss rate and ROIs per image (ROIPI) to assess the performance of the segment-based ROI generation module.

We present a region of interest (ROI) generation method specialized for nighttime pedestrian detection using far-infrared (FIR) images. Because pedestrians typically appear brighter than background in FIR images, previous research efforts primarily attempted to extract ROIs based on the intensity threshold. However this approach has problems resulting from the intensity variances of pedestrians due to their clothing and, especially in urban scenarios, and other heat sources that emit more heat than the pedestrians. In this paper, we propose a novel ROI generation method that is based on combining image segments instead of using the intensity threshold. In order to minimize dependence on brightness, we utilize the low-frequency characteristics of FIR images. As a result, our proposed method generates a small number of ROIs at an acceptable miss rate and the generated ROIs provide advantages for classification because the pedestrians are satisfactorily arranged within a bounding box. Experiments conducted indicate that our proposed method performs reliably in urban scenarios.