论文标题
空中激光点云的增强语义签名以进行比较
Augmented Semantic Signatures of Airborne LiDAR Point Clouds for Comparison
论文作者
论文摘要
激光点云提供了丰富的几何信息，这对于对城市地区复杂场景的分析特别有用。在同一区域中发现两个不同的三维点云之间的结构和语义差异是一个重要的问题。点云的比较涉及计算昂贵的注册和分段。我们有兴趣在没有注册过程的情况下捕获点云的几何不确定性和语义内容的相对差异。因此，我们提出了点云的方向 - 几何标志，该标志集成了其概率的几何和语义分类。我们研究几何签名的不同特性，这是基于图像的几何不确定性和语义含量的编码。我们探索不同的指标，以确定这些签名之间的差异，这反过来又比较了点云而不执行点对点注册。我们的结果表明，特征的差异与点云的几何和语义差异证实了。
LiDAR point clouds provide rich geometric information, which is particularly useful for the analysis of complex scenes of urban regions. Finding structural and semantic differences between two different three-dimensional point clouds, say, of the same region but acquired at different time instances is an important problem. A comparison of point clouds involves computationally expensive registration and segmentation. We are interested in capturing the relative differences in the geometric uncertainty and semantic content of the point cloud without the registration process. Hence, we propose an orientation-invariant geometric signature of the point cloud, which integrates its probabilistic geometric and semantic classifications. We study different properties of the geometric signature, which are an image-based encoding of geometric uncertainty and semantic content. We explore different metrics to determine differences between these signatures, which in turn compare point clouds without performing point-to-point registration. Our results show that the differences in the signatures corroborate with the geometric and semantic differences of the point clouds.
