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A Multi-View Dense Point Cloud Data Fusion Method Based on Bilateral Filter

A bilateral filter and dense point cloud technology, applied in image data processing, electrical digital data processing, special data processing applications, etc., can solve problems such as low efficiency and inability to guarantee point clouds

Active Publication Date: 2017-01-11
XIDIAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

On the one hand, the incremental fusion method is inefficient, and on the other hand, it cannot guarantee that the fused point cloud is located on the optimal surface

Method used

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  • A Multi-View Dense Point Cloud Data Fusion Method Based on Bilateral Filter
  • A Multi-View Dense Point Cloud Data Fusion Method Based on Bilateral Filter
  • A Multi-View Dense Point Cloud Data Fusion Method Based on Bilateral Filter

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Embodiment 1

[0060] The present invention proposes a multi-view dense point cloud data fusion method, such as figure 1 shown. When fusing multiple pieces of multi-view dense point cloud data, the first step is to input multi-view dense point cloud data. The input multi-view dense point cloud data is required to contain both 3D coordinate information and normal vector information. That is to say, each point data in the input multi-view dense point cloud p=(v,n), where v=(v x ,v y ,v z ) represents a three-dimensional coordinate vector, n=(n x ,n y ,n z ) represents a normal vector.

[0061] After inputting the multi-view dense point cloud data, before proceeding to the second step of topological relationship construction, it is necessary to calculate the average point distance D of the multi-view dense point cloud data for later use. The calculation method of the average point distance D of multi-view dense point cloud data is as follows:

[0062] 1) Randomly select a piece of poin...

Embodiment 2

[0092] Below in conjunction with concrete simulation experiment, the present invention is described, and wherein the present invention method realizes corresponding algorithm on VS2010 and opengl platform and runs on the PC of Intel i7-4770CPU 3.4GHz, 16GB internal memory.

[0093] Figure 3(a) shows the head point cloud data with overlapping parts of the three viewing angles, which contains a total of 657,088 3D point data. In order to show the overlapping area more clearly, Fig. 3(b) is an enlarged view of the part circled in the box in Fig. 3(a). Figure 3(c) is the fused point cloud data, which contains a total of 306803 point data. Fig. 3(d) is an enlarged view of the part in the box circle in Fig. 3(c) (corresponding to Fig. 3(b), in order to show more clearly the effect of fusion of the overlapped area). This example can also illustrate that the method of the present invention can quickly fuse multi-viewpoint dense point cloud data into a complete, single-layer, smooth, ...

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Abstract

The invention discloses a multi-view dense point cloud data fusion method based on a two-sided filter and belongs to the technical field of optical three-dimensional non-contact measurement. The multi-view dense point cloud data fusion method based on the two-sided filter comprises the steps that (1) multi-view dense point cloud data are input, (2) a topological relation is established, (3) point data classification is conducted based on the two-sided filter, (4) Mean-shift clustering fusion is conducted, and (5) a fusion result is output. When the method is used for fusing the multi-view dense point cloud data, the two-sided filter and the Mean-shift clustering are introduced, recognition of an overlapping region and a non-overlapping region is not needed, in this way, the efficiency of fusing a great number of multi-view dense point cloud data is improved, the smoothness of a point cloud obtained after fusion are improved, and the defects of an existing point cloud fusion technology are effectively overcome.

Description

technical field [0001] The invention belongs to the technical field of optical three-dimensional non-contact measurement, relates to a multi-viewpoint dense point cloud data fusion method, and further relates to a new multi-viewpoint dense point cloud data fusion method based on a bilateral filter. Background technique [0002] Optical three-dimensional measurement technology is an intelligent and visualized high-tech integrating optical, mechanical, electrical and computer technologies. It is mainly used to scan the shape and structure of the object space to obtain the three-dimensional outline of the object and obtain the three-dimensional surface points of the object. spatial coordinates. With the progress of modern detection technology, especially with the development of high-tech such as laser technology, computer technology and image processing technology, three-dimensional measurement technology has gradually become the focus of people's research. Due to the advantag...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06F17/30G01B11/00
Inventor 史宝全
Owner XIDIAN UNIV
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