Air-to-ground multimodal object detection algorithm based on feature association learning

Dongfang Yang,Xing Liu,Yongfei Li,Hao He

doi:10.1177/1729881419842995

Abstract

Detecting objects on unmanned aerial vehicles is a hard task, due to the long visual distance and the subsequent small size and lack of view. Besides, the traditional ground observation manners based on visible light camera are sensitive to brightness. This article aims to improve the target detection accuracy in various weather conditions, by using both visible light camera and infrared camera simultaneously. In this article, an association network of multimodal feature maps on the same scene is used to design an object detection algorithm, which is the so-called feature association learning method. In addition, this article collects a new cross-modal detection data set and proposes a cross-modal object detection algorithm based on visible light and infrared observations. The experimental results show that the algorithm improves the detection accuracy of small objects in the air-to-ground view. The multimodal joint detection network can overcome the influence of illumination in different weather conditions, which provides a new detection means and ideas for the space-based unmanned platform to the small object detection task.

Highlights

The object detection technology under the air-to-ground field of view is a special but widely used application of multi-object detection technology
In order to validate the environmental adaptability of detection algorithm, different light conditions are involved in our data sets
Air-to-ground object detection are of critical technologies in various application in either military or civilian fields

Summary

Introduction

The object detection technology under the air-to-ground field of view is a special but widely used application of multi-object detection technology. In air-to-ground applications, the scale of view is large, and the target of interest tends to be rather small, which will bring new difficulties in object detection.[1,2,3,4] In the military field, object detection can be directly applied to tasks such as battlefield investigation, situation analysis, air-to-ground target strike, and object tracking. Air-to-ground object detection can be directly applied to various tasks, such as traffic monitoring, natural disaster analysis, and agricultural ecological management.

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