This paper presents a High-altitude infrared thermal dataset, HIT-UAV, for
object detection applications on Unmanned Aerial Vehicles (UAVs). HIT-UAV
contains 2898 infrared thermal images extracted from 43470 frames. These images
are collected by UAV from schools, parking lots, roads, playgrounds, etc.
HIT-UAV provides different flight data for each place, including flight
altitude (from 60 to 130 meters), camera perspective (from 30 to 90 degrees),
date, and daylight intensity. For each image, the HIT-UAV manual annotates
object instances with two types of the bounding box (oriented and standard) to
address the challenge that object instances have a significant overlap in
aerial images. To the best of our knowledge, HIT-UAV is the first publicly
available high-altitude infrared thermal UAV dataset for persons and vehicles
detection. Moreover, we trained and evaluated the benchmark detection
algorithms (YOLOv4 and YOLOv4-tiny) on HIT-UAV. Compared to the visual light
dataset, the detection algorithms have excellent performance on HIT-UAV because
the infrared thermal images do not contain a significant quantity of irrelevant
information with detection objects. This indicates that infrared thermal
datasets can significantly promote the development of object detection
applications. We hope HIT-UAV contributes to UAV applications such as traffic
surveillance and city monitoring at night. The dataset is available at
this https URL.

该研究提出了一个用于无人机（UAV）物体检测应用的高空红外热数据集 HIT-UAV，其中包含来自学校、停车场、道路、游乐场等地采集的 2898 个红外热图像，将有助于提高 UAV 应用的性能。