Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Method for generating large batch of point cloud data sets

A point cloud data, large-scale technology, applied in image data processing, 3D modeling, instruments, etc., can solve problems such as difficulty in obtaining point cloud, difficulty in 3D point cloud, scarcity of point cloud data sets, etc.

Pending Publication Date: 2021-03-26
SOUTH CHINA UNIV OF TECH
View PDF0 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But the difference is that the training data sets of neural networks currently used to process two-dimensional images come from a wide range of sources, while the acquisition of three-dimensional point clouds is much more difficult than that of two-dimensional images. The point cloud data sets used to train neural networks Currently even more scarce
For some special application scenarios, it is more difficult to obtain point clouds

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 more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for generating large batch of point cloud data sets
  • Method for generating large batch of point cloud data sets
  • Method for generating large batch of point cloud data sets

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0041] A method for generating large batches of point cloud datasets such as figure 1 As shown, it is specially aimed at solving the problem of scarcity of data sets during the training of neural network based on point cloud processing, so that the performance of point cloud processing algorithm based on neural network has been improved. figure 2 In order to generate the flow of the data set and the corresponding example diagram, the main steps are modeling, converting the model into a point cloud on the surface of the object, synthesizing the point cloud of each part of the scene, and subsequent processing; including the following steps:

[0042] Create a 3D model of the objects in the scene;

[0043] Use the 3D model to sample points to form the surface point cloud of the 3D model;

[0044] Combine the surface point clouds of each component in the scene to generate combined surface point cloud information;

[0045]Post-process the point cloud information of the combined s...

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

No PUM Login to View More

Abstract

The invention discloses a method for generating large batch of point cloud data sets. The method comprises the following steps: establishing a three-dimensional model for an object in a scene; re-sampling points for each vertex and each patch in the three-dimensional model to form a surface point cloud of the three-dimensional model; combining the surface point clouds of components in the scene togenerate scene point cloud information; processing the scene point cloud information by adopting a simulated camera model to form simulated scene point cloud information acquired by a simulated structured light system; generating a large batch of point cloud data sets by repeating for many times. According to the method, the training data volume of a neural network for point cloud processing is improved, and meanwhile, the method has pertinence for specific scenes and processing tasks, so that the performance of the neural network is improved.

Description

technical field [0001] The invention relates to the research field of machine vision, in particular to a method for generating large batches of point cloud data sets. Background technique [0002] At present, point cloud data processing is a relatively popular field in the field of machine vision. As a kind of three-dimensional data, point cloud can provide detailed three-dimensional information for objects and environments. Its data processing is an important aspect of three-dimensional vision technology. There are many applications in the field. [0003] Inspired by deep learning and the ability of neural networks to learn features in 2D images, neural network-based point cloud processing methods are currently being developed. But the difference is that the training data sets of neural networks currently used to process two-dimensional images come from a wide range of sources, while the acquisition of three-dimensional point clouds is much more difficult than that of two-...

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
no application Login to View More
IPC IPC(8): G06T17/00G06T19/20G06T5/00
CPCG06T17/00G06T19/20G06T2207/10012G06T5/70
Inventor 王念峰林景新张宪民
Owner SOUTH CHINA UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products