The invention discloses an intelligent automobile traffic scene mapping method considering a dynamic target, and the method comprises the steps: 1, dividing intelligent automobile traffic scene targets into a high-dynamic object type, a low-dynamic object type, a semi-static object type and a static object type, carrying out the analysis, and carrying out the target detection through a target detection algorithm; 2, performing motion consistency detection on feature points in a traffic scene by adopting an LK optical flow algorithm, screening out dynamic feature points, and screening dynamic targets in a target detection result obtained in the step 1; and step 3, integrating the dynamic target information obtained in the step 2 into an SLAM system, removing feature points in a dynamic target frame in feature matching, and establishing an intelligent automobile traffic scene sparse point cloud map by using static feature points. According to the method, the traffic scene map is constructed by using the intelligent vehicle-mounted camera, so that the influence of a dynamic target in the traffic scene on the mapping precision is reduced, and the method has relatively high real-time performance in mapping.
本发明公开了一种考虑动态目标的智能汽车交通场景建图方法,包括:步骤1、将智能汽车交通场景目标分为高动态物体、低动态物体、半静态物体和静态物体几种类型进行分析,利用目标检测算法进行目标检测;步骤2、采用LK光流算法对交通场景中特征点进行运动一致性检测,筛选出动态特征点,筛选步骤1所得到的目标检测结果中的动态目标;步骤3、将步骤2得到的动态目标信息融入SLAM系统,剔除特征匹配中动态目标框内特征点,利用静态特征点建立智能汽车交通场景稀疏点云地图。本发明利用智能汽车车载相机构建出交通场景地图,降低了交通场景中动态目标对建图精度的影响,具有较强的在建图实时性。
Intelligent automobile traffic scene mapping method considering dynamic target
一种考虑动态目标的智能汽车交通场景建图方法
2024-03-05
Patent
Electronic Resource
Chinese
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