关键词: 全景车辆检测, SSD算法, 特征融合, 传输转换模块

Abstract:

To address the issue that the performance of the Single Shot Multi-Box Detector（SSD） algorithm is suffering from low accuracy and high missed detection rate when detecting vehicle targets in panoramic video images, this paper constructs an improved SSD network architecture named R-SSD, and proposes a vehicle target detection algorithm in panoramic video image based on the proposed R-SSD. An RPN* network is added before the original SSD network, which can filter the prior box of negative samples, and roughly adjust the position and size of the prior box to provide good initial conditions for subsequent regression. A transmission conversion module is constructed between the original SSD and RPN* network to realize feature fusion between these two networks, and increase the low-level feature information, so as to improve the detection effect of the target. The comparative experiment results on panorama video image data set show that the proposed algorithm has a detection accuracy of 90.78%, which is significantly better than the SSD algorithm, and has higher detection rate and lower missing detection rate than the traditional SSD network in panoramic target vehicle detection.

Key words: panoramic vehicle object detection, Single Shot Multi-Box Detector（SSD） algorithm, feature fusion, transmission conversion module