关键词: 无人机图像, SSD, 目标检测

Abstract:

Fast and accurate pedestrian and vehicle detection in UAV images is a meaningful but challenging task, which is widely used in military reconnaissance, traffic control and remote area rescue missions. However, UAVs are small mobile devices with limited memory and computing power, it is a real?challenge?for?real-time object detection on a UAV platform. Aiming at the problem that the SSD algorithm is too large and the operation memory consumption is too high to run on the UAV platform, a lightweight backbone network is carefully designed which reduces the number of channels and convolution of the original network, so as to reduce the number of parameters of the network. In addition, aiming at the problem of small object and complex scene in UAV scene, a lightweight receptive field block is proposed to enhance the feature representation ability, and the detection accuracy?of small object is further improved by combining context information module. Experimental results show that the proposed algorithm has high accuracy and real-time performance in the tasks of pedestrian and vehicle detection from UAV images.

Key words: Unmanned Aerial Vehicle（UAV） images, Single-Shot Detector（SSD）, object detection