户外导盲动态障碍目标RGB-D视觉感知与探测  

Outdoor Navigation for Blind People Dynamic Obstacle Target RGB-D Visual Perception and Detection

作　　者：廉悦 刘德儿[1] LIAN Yue;LIU Deer(School of Civil and Surveying Engineering,Jiangxi University of Science and Technology,Ganzhou 341000,China)

机构地区：[1]江西理工大学土木与测绘工程学院,江西赣州341000

出　　处：《电子科技》2024年第12期9-16,23,共9页Electronic Science and Technology

基　　金：国家自然科学基金(42271434);江西省自然科学基金(S2020ZRMSB0257)。

摘　　要：针对无障碍设施设计不合理、建设不完全、导盲辅具参差不齐、功能单一以及无法满足用户户外出行需求等问题,文中提出了一种利用BlendMask算法并基于RGB-D户外导盲动态障碍目标的视觉感知与探测的方法。该方法使用Azure Kinect DK采集的RGB-D数据,利用6组实例分割算法对比,选择效果最优的BlendMask实例分割模型,通过添加深度数据处理分支得到单个实例的深度信息,即目标到相机的距离。为提高距离检测精度,通过三维,以点云的形式使用离群点剔除操作,去除分割掩膜中残余的背景信息。其中,基于统计的离群点剔除方法能更准确地检测障碍物到相机的距离。实验结果表明,该方法不仅能较好地检测户外动态目标,也能检测目标到相机的距离,提高了距离检测的精度。In view of the problems such as unreasonable design,incomplete construction of barrier-free facilities,uneven guide AIDS,single functions and inability to meet users'outdoor travel needs,this study proposes a visual perception and detection method based on BlendMask algorithm and RGB-D dynamic obstacle targets for outdoor guide for the blind.The proposed method uses RGB-D data collected by Azure Kinect DK,compares six sets of instance segmentation algorithms,selects the best BlendMask instance segmentation model,and adds a depth data processing branch to obtain the depth information of a single instance,that is the distance from the target to the camera.To improve distance detection accuracy,outlier rejection operations are used in 3D,in the form of point clouds,to remove residual background information from the segmentation mask,where a statistically based outlier rejection method can more accurately detect the distance from the obstacle to the camera.Experimental results show that the proposed method is not only better at detecting dynamic outdoor targets,but also detects the distance from the target to the camera and improves the accuracy of distance detection.

关 键 词：户外 盲人导航 实例分割 RGB-D 距离检测 离群点剔除 BlendMask 深度学习 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]