面向航空影像下车辆目标的实时检测算法

Real-time detection algorithm for vehicle targets in aerial images

为解决自然场景下的通用目标检测框架对航空影像下的小车辆目标检测性能不足的缺陷,提出一种专用于航空影像下的小车辆目标实时检测器,即轻量级尺度公平单卷积检测器(lightweight scale fair single convolution detector,LSFSCD)。相比传统检测方法和基于CNN的通用检测等方法,其架构更加简单,模型更小。该架构减少了误检和错检,实现更高检测精度的同时减少训练时间。通过使用Caffe框架在8g显存GTX1080上对VEDAI和DLR数据集进行实验,其结果验证了所提算法的有效性。

To solve the shortcomings of the general target detection framework in natural scenes,such as the lack of small vehicle target detection performance in aerial image,a real-time detector for small vehicle targets dedicated to aerial imagery was proposed,which was a lightweight scale fair single convolution detector (LSFSCD). Compared with traditional detection methods and general detection methods based on CNN,the architecture is simpler and the model is smaller. This architecture reduces false detections and false positives,enabling higher detection accuracy and using less training time. The effectiveness of the proposed algorithm is verified by experimenting on VEDAI and DLR data sets on 8g memory GTX1080 using Caffe framework.