Water surface object detection using panoramic vision based on improved single-shot multibox detector

EURASIP Journal on Advances in Signal Processing

Jiawei Xia¹  Xufang Zhu²  Shuo He²  Aofeng Li² 

[1] College of Armamente Engineering, Naval University of Engineering, 430000, Wuhan, China;College of Electronic Engineering, Naval University of Engineering, 430000, Wuhan, China;

关键词: Panoramic vision;    SSD;    Deconvolution;    Feature pyramid;   

DOI  :  10.1186/s13634-021-00831-6

来源: Springer

【 摘 要 】

In view of the deficiencies in traditional visual water surface object detection, such as the existence of non-detection zones, failure to acquire global information, and deficiencies in a single-shot multibox detector (SSD) object detection algorithm such as remote detection and low detection precision of small objects, this study proposes a water surface object detection algorithm from panoramic vision based on an improved SSD. We reconstruct the backbone network for the SSD algorithm, replace VVG16 with a ResNet-50 network, and add five layers of feature extraction. More abundant semantic information of the shallow feature graph is obtained through a feature pyramid network structure with deconvolution. An experiment is conducted by building a water surface object dataset. Results showed the mean Average Precision (mAP) of the improved algorithm are increased by 4.03%, compared with the existing SSD detecting Algorithm. Improved algorithm can effectively improve the overall detection precision of water surface objects and enhance the detection effect of remote objects.

【 授权许可】

CC BY