A Forward Train Detection Method Based on Convolutional Neural Network

Forward train detection is of great significance to improve train safety. In this paper, a vision-based method is proposed for forward train detection. The proposed method based on CenterNet, a novel object detection network, to realize accurate and fast forward train detection. The forward train detection network is divided into two stages: downsampling stage and center points generation stage. In downsampling stage, a full convolution network is performed to downsample the image, meanwhile to extract the feature of the image. In the center points generation stage, three branch networks are used to predict the bounding box of the forward train, including heatmaps generation branch, center offset regression branch and forward train bounding box size regression branch. Experiments results show that the proposed method can detect the forward train well and achieve 30.7% Average Precision (AP) with a 47.6 Frames Per Second (FPS).