Method for Rapidly Extracting Indoor 3D Line Segment Structure Based on Point Cloud Data
A point cloud data and extraction room technology, applied in image data processing, image analysis, image enhancement, etc., can solve the problems of threshold setting relying on experience, high memory consumption, over-segmentation, etc., to reduce the amount of processed data and overcome over-segmentation The effect of segmentation and precise extraction
Active Publication Date: 2022-04-29
WUHAN UNIV
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Problems solved by technology
At present, the method based on the plane is better, that is, first segment the plane from the point cloud, and then extract the contour points and three-dimensional line segments from the plane, but the traditional plane segmentation algorithm has problems such as low efficiency, over-segmentation, under-segmentation, high Memory consumption, threshold setting depends on experience, etc.
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[0059] The specific implementation of the method for quickly extracting indoor three-dimensional line segment structure based on point cloud data according to the present invention will be described in detail below with reference to the accompanying drawings.
[0060]
[0061] In this embodiment, the solution is described by taking the extraction of the three-dimensional line segment structure in the Wuhan Haida Cloud as an example. Specifically, such as figure 1 As shown, the method for quickly extracting indoor three-dimensional line segment structure based on point cloud data provided by this embodiment includes the following steps:
[0062] Step 1. First, focus on Faru s 150 ground 3D laser scanner for leveling operation, and then scan the activity room on the first floor of Wuhan Haida Digital Cloud Company to obtain indoor point cloud data P orig , a total of 2,154,851 points were obtained, see figure 2 (a), next to P orig Perform spatial uniform downsampling, so...
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The present invention provides a method for quickly extracting indoor three-dimensional line segment structure based on point cloud data, comprising: measuring and collecting point cloud data of indoor buildings, performing projection to form two-dimensional projected point cloud data; extracting line segments in the two-dimensional projected point cloud data, The spatial geometric equation of the facade is calculated by using the coordinates of the end points of the line segment, and then the facade is segmented; the facade points are removed from the two-dimensional projection point cloud data, the remaining points are down-sampled and the horizontal plane is segmented, and the facade and the horizontal plane are combined to obtain The final plane segmentation result; for each extracted plane in the plane segmentation result, the precise parameters of the plane are fitted, the points on the plane are projected onto the fitted fitting surface, and the edge points of each plane are extracted to obtain the edge Point collection; set the farthest distance from a point to a straight line, extract 3D line segments, and further merge line segments according to the parallelism, collinearity, and coincidence between line segments to obtain the final 3D line segment structure extraction result.
Description
technical field [0001] The invention belongs to the technical field of three-dimensional laser scanning, and in particular relates to a method for quickly extracting an indoor three-dimensional line segment structure based on point cloud data. Background technique [0002] In recent years, 3D lidar technology has developed rapidly, and large-scale and high-density point cloud data are easy to obtain. At the same time, massive point clouds have brought great challenges to data processing and information extraction. Due to the unstructured, irregular, and non-uniform characteristics of raw point cloud data, it is necessary to abstract it concisely and meaningfully. As one of the most common features of the real environment, the line segment structure plays an important role in many fields such as 3D reconstruction, registration, positioning, calibration, road extraction, and object recognition. [0003] At present, point cloud 3D line segment structure extraction is still an ...
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IPC IPC(8): G06T17/20G06T17/10G06T7/136G06K9/62G06V10/762
CPCG06T17/20G06T17/10G06T7/136G06T2207/10028G06F18/23
Inventor田朋举花向红
OwnerWUHAN UNIV