Graph theory based three-dimensional point cloud data plane extracting method
A technology of 3D point cloud and data plane, which is applied in the field of 3D point cloud data plane extraction based on graph theory to achieve the effect of improving accuracy
Active Publication Date: 2013-02-27
TONGJI UNIV
View PDF1 Cites 14 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
At the same time, due to the inherent physical limitations of the camera and the inevitable noise in the data acquisition process, the 3D point cloud usually contains noise, outliers and holes. Planar and high-precision planar extraction is somewhat challenging
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment
[0029] A 3D point cloud data plane extraction method based on graph theory, the method first constructs a graph, each vertex in the graph corresponds to a data point in the 3D point cloud, and the edges on the graph pass through K-nearest neighbors (K-Nearest Neighbor, KNN) algorithm is calculated; Simultaneously, calculate the plane normal vector of each point in the three-dimensional point cloud, the present embodiment uses a kind of weighted local plane fitting method to estimate the plane normal vector of each point.
[0030] Then, calculate the weight value corresponding to each edge in the graph, that is, the normal vector difference between the two vertices corresponding to each edge, and arrange all the edges in ascending order of weight value, so that the edge with the smaller normal vector difference will be ranked In the front; at the same time, assign an initial threshold to each vertex in the graph.
[0031] Next, for each edge on the graph, if the corresponding t...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More PUM
Login to View More Abstract
The invention relates to a graph theory based three-dimensional point cloud data plane extracting method, which comprises the following steps: firstly constructing a graph, corresponding each vertex in the graph to a data point in the three-dimensional point cloud, and calculating out the borders of the graph through a k-nearest neighbor method; at the same time, using a weighted partial plane fitting method to calculate plane normal vectors of each point; then, calculating the weighted value corresponding to each border, namely a difference value of the normal vectors of two vertexes corresponding to each border, and assigning an initial threshold value to each vertex in the graph; as for each border in the graph, if the difference value of the normal vectors is not larger than any one of the two regional threshold values, combining the two regions, wherein the threshold value of the new region is equal to the difference value of the normal vectors plus the initial value and dividing quantity of data points in the new region; and at last, as for each region, if the quantity of the data points is larger than the set threshold value, then determining that the region is a plane. Compared with the prior art, the method has the advantages of high plane extracting precision and strong noise interference prevention performance.
Description
technical field [0001] The invention relates to a point cloud data processing method, in particular to a graph theory-based three-dimensional point cloud data plane extraction method. Background technique [0002] Semantic maps are a long-term goal for mobile robots to understand the environment, and indoor environments usually contain many planes, so plane extraction or plane segmentation is a prerequisite for building semantic maps and understanding the environment. In general, plane extraction is the problem of detecting planes from a set of 3D points. At present, the commonly used methods for plane extraction are methods based on plane mathematical models, such as the random sampling consistency (RANdom SAmple Consensus, RANSAC) method and the Hough Transform Method (Hough Transform Method), these methods can be extracted from 3D point cloud data A plane that fits the mathematical model of a plane, but it is not possible to determine whether the plane actually exists in...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More Application Information
Patent Timeline
Login to View More Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 王廷旗陈启军
Owner TONGJI UNIV