Three-dimensional point cloud outlier elimination method based on image segmentation
A 3D point cloud and image segmentation technology, applied in image analysis, 3D image processing, image enhancement and other directions, can solve problems such as large amount of calculation, a large number of manual interactions, application-dependent scenarios, etc., to solve the lack of semantics, reduce Computational amount, more realized effect
A 3D point cloud and image segmentation technology, applied in image analysis, 3D image processing, image enhancement and other directions, can solve problems such as large amount of calculation, a large number of manual interactions, application-dependent scenarios, etc., to solve the lack of semantics, reduce Computational amount, more realized effect
CN111127622AActive Publication Date: 2020-05-08ZHEJIANG UNIV
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[0028] see figure 1 and Figure 8 , the method for removing outliers in the 3D point cloud based on image segmentation in the present embodiment comprises the following steps:
[0029] S1, the projection direction is generated by uniform sampling in the unit sphere parameter space. The spherical parameter equation used in the present invention is as follows:
[0030]
[0031] figure 2 (a) is a schematic diagram of spherical parameter coordinates used in the present invention, wherein θ is the clockwise angle between the positive direction of the X axis and the direction of the data point position vector, and It is the angle formed by the negative direction of the Z axis and the position vector of the data point. figure 2 (b) In order to select the sampling interval as Δθ=π / 5, The distribution map of the sampling points obtained, and the position vectors corresponding to these sampling points can be used as the projection direction of the perspective projection.
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The invention discloses a three-dimensional point cloud outlier elimination method based on image segmentation, which belongs to the field of computer graphics, and comprises the following steps: setting a sampling interval, and performing uniformly sampling in a unit sphere parameter space to generate a projection direction; solving a transformation matrix according to a 313 rotation relationshipbetween the generated projection direction and a Z axis of a world coordinate system where the three-dimensional point cloud is located, and performing attitude transformation on the point cloud by utilizing the transformation matrix; calculating the image resolution of the three-dimensional point cloud after attitude transformation projected to the perspective projection virtual view; obtainingperspective projection virtual views of the three-dimensional point cloud in all projection directions; segmenting a main body part of the image in the obtained perspective projection virtual view byutilizing a main body extraction algorithm based on image segmentation; according to a visible shell technology, forming a convex hull of a three-dimensional point cloud by utilizing a side shadow contour line of a main body part in a perspective projection virtual view, and taking three-dimensional points except the convex hull of the three-dimensional point cloud as outliers to be eliminated.
Description
technical field [0001] The invention relates to the field of computer graphics, in particular to a method for removing outliers in a three-dimensional point cloud based on image segmentation. Background technique [0002] The 3D point cloud obtained from a laser scanner or camera usually contains a large number of outliers due to factors such as illumination, calculation errors, and equipment errors, and the existence of these outliers will greatly affect the accuracy of subsequent 3D point cloud processing. Therefore, before the subsequent 3D point cloud processing, the outlier points in the 3D point cloud need to be eliminated first. [0003] In the field of computer graphics, the preprocessing of 3D point clouds has been receiving extensive attention. The main issues involved in the preprocessing steps of 3D point cloud are the elimination of outliers, the removal of noise, and the preservation of point cloud features. However, there is no uniform definition of outliers...
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Patent Timeline
08 May 2020
Publication
CN111127622A
- IPC
- G06T15/30; G06T7/10; G06T3/00
- CPC
- G06T15/30; G06T7/10; G06T2207/10012; G06T3/06
- Inventors
- 冯结青; 葛林林