Locality preserving PCA-based three-dimensional point cloud registration method

A 3D point cloud and local preservation technology, applied in the field of 3D reconstruction, can solve problems such as the inability to extract local structural features

Inactive Publication Date: 2018-03-13
BEIJING UNION UNIVERSITY
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Problems solved by technology

However, the PCA point cloud registration algorithm only considers the overall s

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  • Locality preserving PCA-based three-dimensional point cloud registration method
  • Locality preserving PCA-based three-dimensional point cloud registration method
  • Locality preserving PCA-based three-dimensional point cloud registration method

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[0030] The superiority of the present invention compared to other algorithms is verified below in conjunction with examples.

[0031] Such as Image 6 As shown, the present invention provides a 3D point cloud registration method based on PCA. First, the K-nearest neighbor criterion is used to judge whether the points in the complete 3D point cloud data of the object are adjacent, and the adjacency is generated according to the K-nearest neighbor criterion. Figure and complementary graph, construct weight matrix; then use PCA algorithm for feature extraction, obtain the eigenvectors corresponding to the eigenvalues ​​and sort the eigenvalues ​​from large to small, and select the features corresponding to the top r eigenvalues The vector constructs the feature matrix; finally, the conversion parameters are obtained according to the feature matrix, and the coordinates are normalized to complete the registration of the 3D point cloud.

[0032] In order to verify the accuracy and e...

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Abstract

The invention discloses a locality preserving PCA-based three-dimensional point cloud registration method. In order to preserve local features of a point cloud, an LPP (Locality Preserving Projection)thought is adopted, and an adjacency graph and a complement graph of the point cloud are constructed through a K-neighbor criterion; adjacent points and non adjacent points are subjected to feature extraction in different processing modes; a conversion parameter is calculated through a feature matrix; and coordinate normalization is performed to finish registration. By adopting the technical scheme, a relatively good effect is achieved in registration of the point cloud with a remarkable local feature structure.

Description

technical field [0001] The invention belongs to the technical field of three-dimensional reconstruction, and in particular relates to a three-dimensional point cloud registration method based on PCA. Background technique [0002] The 3D laser scanner adopts the laser ranging method, which can efficiently obtain the 3D data of the target. In order to obtain the complete 3D point cloud data of the object, it is necessary to convert the point cloud data from different perspectives into the same coordinate system through data registration. 3D point cloud registration is an important part of 3D reconstruction, and it has been widely used in reverse engineering, computer vision and other fields. Point cloud registration methods are divided into manual registration, instrument-dependent registration and automatic registration. At present, automatic registration is mainly divided into three types: registration based on feature finding correspondence, registration based on statisti...

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Application Information

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IPC IPC(8): G06T7/33G06K9/62
CPCG06T7/33G06T2207/10028G06F18/2135
Inventor 王育坚高倩谭卫雄吴明明
Owner BEIJING UNION UNIVERSITY
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