Efficient pedestrian detection with enhanced object segmentation in far IR night vision

摘要

This paper presents a pedestrian detection system with enhanced object segmentation procedure working on a far infrared (FIR) video. To make the object detection more accurate on the FIR images, we propose an enhanced segmentation procedure with two thresholds and the region enlargement. This combination allowed a significant reduction of the region of interests (ROIs) for further processing. Experiments performed on demanding public dataset show a significant increase of the pedestrian detection performance (up to 33 frames per second) with the accuracy comparable with state-of-the-art algorithms.