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Three-dimensional point cloud restoration method for graphic processing

A 3D point cloud and graphics processing technology, applied in image data processing, neural learning methods, image enhancement, etc., can solve problems such as fragility, and achieve the effect of improving repair performance, reducing noise and deformation, and the method system is efficient and practical

Pending Publication Date: 2021-05-11
NANJING UNIV
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Problems solved by technology

[0007] (3) When these parameter settings are applied to new models that the network has not seen, the parameter settings may be statistically vulnerable

Method used

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  • Three-dimensional point cloud restoration method for graphic processing
  • Three-dimensional point cloud restoration method for graphic processing
  • Three-dimensional point cloud restoration method for graphic processing

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Embodiment

[0074] The object task of the present invention is as Figure 1a and Figure 1b as shown, Figure 1a For the original model that needs to be repaired, Figure 1b For the repaired model, the self-attention module structure system of the method of the present invention is as follows figure 2 As shown, the structure of the whole global feature extractor is as follows image 3 shown. Each step of the present invention is described below according to an embodiment.

[0075] Step (1), collect data to the input point cloud model data set;

[0076] Step (1.1), set the input of a single 3D point cloud model s, and preset 5 viewpoints, which are (1, 0, 0), (0, 0, 1), (1, 0, 1), (- 1, 0, 0), (-1, 1, 0), multiple different viewpoints to ensure that the missing part of the incomplete model is random when collecting training and testing data;

[0077] Step (1.2), randomly select a viewpoint as the center point p, and preset a radius r (the radius is set according to the number of r...

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Abstract

The invention provides a three-dimensional point cloud restoration method for graphic processing. The method comprises the following steps: step 1, collecting data from an input point cloud model data set; 2, combining a method based on a Self-Attention self-attention mechanism with a multilayer perceptron (MLP) to obtain a long-distance dependency extraction network, mapping the input point cloud into a global feature vector by using the long-distance dependency extraction network, and generating a missing part of the incomplete point cloud by using a decoder of a topological root tree structure; and step 3, synthesizing the incomplete point cloud and the generated missing part point cloud together to obtain a final repaired complete point cloud model.

Description

technical field [0001] The invention belongs to the fields of computer three-dimensional model processing and computer graphics, and in particular relates to a three-dimensional point cloud restoration method for graphics processing. Background technique [0002] In recent years, to directly acquire a large amount of 3D data in the real world can be achieved by using LiDAR scanners or depth sensors such as Kinect, as well as stereo cameras, etc. [0003] However, the 3D data obtained with these instruments are often incomplete due to the following reasons: the limited viewing angle of the scanner, occlusion by non-target objects, and the effects of light refraction and reflection. Therefore, the geometric information and semantic information of the target object are often lost. Therefore, it is a very necessary research topic to study how to repair incomplete 3D models for more subsequent applications. In addition, 3D models also appear in a large number of forms, such as ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T19/20G06N3/08
CPCG06T19/20G06N3/084G06T2207/10028G06T2207/20081G06T2207/20084G06T5/77
Inventor 朱佩浪张岩刘琨
Owner NANJING UNIV
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