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《Optical Technique》 2018-05
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3Dpoint cloud registration algorithm based on locality preserving PCA

WANG Yujian;WU Mingming;GAO Qian;School of Information,Beijing Union University;  
Three-dimensional point cloud registration is an important step to reconstruct three dimension model.The local feature of point cloud can not be retained and the registration effect is influenced when the PCA algorithm is applied to point cloud registration.A 3 Dpoint cloud registration algorithm based on locality preserving PCA is proposed.LPP projection is used to preserve the local characteristics of point cloud.LPP constructs the adjacency graph and its complement of point cloud through K-Nearest Neighbor Criterion.The feature extraction is carried out by using different processing methods for adjacent and non-nearest neighbors.The conversion parameters are obtained by the feature matrix,and the coordinates are normalized to complete point cloud registration.The purpose of finding the conversion parameters after weighting the first three principal components of the eigenvector matrix is to reduce the influence of illumination noise.The experimental results show that the improved algorithm has better effect in registration of the point cloud with obvious local feature structure,and the robustness to lighting noise is improved.
【Fund】: 国家自然科学基金资助项目(61572077)
【CateGory Index】: TP391.41
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