航空影像辅助下的城区机载LiDAR汽车目标检测方法

机载激光雷达(LiDAR)技术的出现为地面汽车目标检测提供了新的途径。为了从机载LiDAR点云数据中提取汽车对象,根据不同地物的属性特征,提出了一种航空影像辅助下的城区机载LiDAR汽车目标检测方法。首先利用形态学开重建滤波完成地面和地物的分类,然后在地物点的基础上结合正射影像,通过归一化植被指数(NDVI)特征完成对植被和非植被地物的初步分类,最后在非植被地物的基础上,根据地物对象的形状特征及高程信息完成汽车和建筑物及阴影植被等非汽车对象的分类,从而完成汽车目标的提取工作。3个实验区的计算结果表明:该方法能有效从LiDAR点云中提取汽车目标,正确度和完整度的均值分别为95%和85%,满足实用性要求。

Automatic Urban Vehicle Detection from Airborne LiDAR Data with Aerial Image

The appearance of LiDAR technology provides a new method for automatic vehicle detection.In order to detect vehicle object from LiDAR data,according to the property features of different objects,a new method of automatic urban vehicle detection from airborne LiDAR data with aerial image is proposed in this paper.Firstly,it is classified ground and non\|ground points using LiDAR filtering with morphological opening by reconstruction.Secondly,with the help of aerial image and its Normalized Differential Vegetation Index (NDVI) feature,it could classify LiDAR non\|ground points into vegetation and non\|vegetation objects.Finally,On the basis of non\|vegetation objects,it could separate vehicle objects automatically from other non\|vehicle objects by shape feature and height property.Three regions has been used to verify the feasibility and reliability of this method.The experiment results show that the proposed method can effectively extract vehicle objects.The mean of correctness and completeness of this method can reach 95% and 85% respectively,which can meet the practical requirements.