光学学报, 2018, 38 (7): 0710004, 网络出版: 2018-09-05   

结合图像语义分割的增强现实型平视显示系统设计与研究 下载: 940次

Design of Augmented Reality Head-up Display System Based on Image Semantic Segmentation
作者单位
长春理工大学光电工程学院, 吉林 长春 130022
摘要
为了提高驾驶员在车辆行驶过程中的安全性,设计了一种结合图像语义分割的增强现实型平视显示(AR-HUD)系统。首先,提出一种改进的单发多框检测器网络对道路场景图像进行语义分割,网络前端采用VGG-16提取图像特征,网络后端对获取的特征图进行上采样,从而对特征图进行像素分割。通过对网络的训练,得到场景目标的像素级分类结果,即环境的语义内容信息。随后,通过分析真实场景、光学显示系统、驾驶员之间的关系,将计算机产生的虚拟信息叠加到真实场景,并将显示内容注册到驾驶员视野中,从而提高行车安全。实验结果表明,语义分割算法的准确率能达到77.8%,虚实注册算法处理每帧图像的时间平均为45 ms,约22 frame·s -1
Abstract
In order to improve the security of drivers, an augmented reality head-up display (AR-HUD) system is designed based on image semantic segmentation. Firstly, we propose an improved single shot multibox detector network for semantic segmentation of road scene images. The front end of the network uses VGG-16 to extract the image features, and the back ends of the network are sampled on the feature maps. Thus, the feature map is segmented. Through the training of the network, the pixel level classification results of the scene objects are obtained, namely, the semantic content information of the environment. Then, with analysis of the relationship among real scene, optical display system, and drivers, the virtual information generated by computer is added to the real scene. In this way, the content is registered into the driver's view to improve the safety of driving. Experimental results show that the accuracy of the semantic segmentation algorithm can reach 77.8%, and image processing time of the algorithm for each frame is 45 ms, in other words, about 22 frame·s -1.

安喆, 徐熙平, 杨进华, 乔杨, 刘洋. 结合图像语义分割的增强现实型平视显示系统设计与研究[J]. 光学学报, 2018, 38(7): 0710004. Zhe An, Xiping Xu, Jinhua Yang, Yang Qiao, Yang Liu. Design of Augmented Reality Head-up Display System Based on Image Semantic Segmentation[J]. Acta Optica Sinica, 2018, 38(7): 0710004.

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