Towards 3D lidar point cloud registration improvement using optimal neighborhood knowledge

By Adrien Gressin, Clément Mallet, Jérôme Demantké, Nicolas David. 2013

205 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Environmental Engineering, Geology, 3D Vision & Pose

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In Environmental Engineering

1. Jyun-Yuan Chen
2. Chung-Hao Chen
3. P. Su
4. Chao Lin

Citations in the corpus

• Eigen-feature analysis of weighted covariance matrices for LiDAR point cloud classification (2014, methodology): “…and eigenvalues can be efficiently obtained by principal component analysis (PCA) (Gross et al., 2007; Mallet et al., 2011; Brodu and Lague, 2012; Gressin et al., 2013), which is a mathematical tool widely used in numerous studies such as point cloud segmentation and reconstruction (Sampath et…”