In recent years, infrared detection technology has developed rapidly, and the characteristics of non-contact and passive detection have made it a research hotspot in the field of military reconnaissance and civilian detection, which has attracted widespread attention from all over the world. Infrared detection technology has been widely used in early warning systems, air defense systems, and coastal defense systems in the military field, and has gradually developed into the civilian field of medical imaging, traffic management, and autonomous driving. Infrared detection, as an important technology in the fields of infrared precision guidance, early warning, video surveillance, search and tracking, has received extensive attention and is of great significance to its research. How to detect small infrared targets is a technical difficulty and research hotspot in the field of infrared detection. In general, the infrared target is small in size, occupies a few pixels in the image, shows a few obvious features, and is easily submerged in background clutter. Although most targets are brighter than the background, the contrast between the target and the background in the original infrared image is very low. In addition, due to the influence of sensor noise and natural factors in infrared images, there are usually many pixel-sized noises, which are similar to high-brightness targets. Infrared thermal images have low signal-to-noise ratio, few texture features, and low resolution, which make infrared target detection more difficult. The robustness, robustness, and real-time performance of current infrared small target detection methods cannot fully meet the needs of different application scenarios. Therefore, infrared small target detection technology is still the focus and difficulty of current research.

In response to this problem, we have created a new infrared aerial photography human-vehicle target recognition database. This database is created by a drone equipped with a professional infrared camera PTZ takes pictures of human-vehicle targets in a variety of different scenarios, and obtains a large number of Infrared image data from a bird’s-eye view angle. The flying height of the drone is about 10-15 meters higher than the ground when shooting. Most of the collected data are small infrared targets, which have a wider monitoring perspective in the monitoring range, which is better than the deployment of instruments in ordinary security scenarios. At different viewing angles, we used the inherent 640*512 resolution of the gimbal to collect more than 10000 infrared images, and then marked the pedestrians, cars, buses, bicycles, cyclists, and trucks that appeared in the images. The database will be mainly used for the research of small target detection and recognition technology in the real-world infrared security field, enabling the further development of infrared small target recognition technology, thereby promoting the application and development of infrared technology in various industries.

The purpose of our research is to establish an infrared small target detection database in a real aerial scene, and verify the actual application effect of the infrared target detection algorithm in a real scene. The database records include pedestrians, cars, buses, bicycles, bicycles, and trucks targets at intersections or roads, company gates, communities, and beaches in different scenarios and at different times. There are a total of 12000 pictures. The database uses person, car, bus, cyclist, bike, and truck as tags for pedestrians, cars, buses, cyclists, bicycles, and trucks, respectively, and uses rectangular boxes to mark the targets in them, with the upper left corner of the picture as Coordinate origin [0,0], use the form of [x1,y1,x2,y2] to record the position of the rectangular frame, x1 represents the abscissa of the upper left corner of the rectangular frame, y1 represents the ordinate of the upper left corner of the rectangular frame, x2 represents the abscissa of the lower right corner of the rectangular box, and y2 represents the ordinate of the lower right corner of the rectangular box. All tag information is saved in the form of xml files.

The researchers

The study was conducted by:

Qing Liu ( qing.liu@iraytek.com )

Zhaofei Xu ( zfxu@iraytek.com )

Shuigen Wang ( shuigen.wang@iraytek.com )

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