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

Point cloud denoising method based on joint bilateral filtering and sharp feature skeleton extraction

A combined bilateral filtering and skeleton extraction technology, applied in image enhancement, instrumentation, computing, etc., can solve difficult problems and achieve the effects of easy usability, good robustness, and good denoising effect

Active Publication Date: 2017-05-24
SOUTH CHINA UNIV OF TECH
View PDF6 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, it is not easy to apply the joint bilateral filtering method to point cloud denoising

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
  • Point cloud denoising method based on joint bilateral filtering and sharp feature skeleton extraction
  • Point cloud denoising method based on joint bilateral filtering and sharp feature skeleton extraction
  • Point cloud denoising method based on joint bilateral filtering and sharp feature skeleton extraction

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0045] The present invention will be further described below in conjunction with specific examples.

[0046] Such as figure 1 As shown, the point cloud denoising method based on joint bilateral filtering and sharp feature skeleton extraction provided in this embodiment includes the following steps:

[0047] 1) Use the normal vector difference method to obtain candidate feature points;

[0048] Calculate the normal vector difference between any two points in the neighborhood of each point and sum them up. When the summation value is greater than a certain threshold, mark this point as a candidate feature point, such as Figure 7a shown.

[0049] 2) Extract the skeleton for the candidate point area;

[0050] use l 1 The median skeleton method calculates the candidate feature point area to obtain the skeleton, such as Figure 7b shown.

[0051] 3) Use the skeleton to resample the candidate points to obtain feature points;

[0052] According to the skeleton obtained in ste...

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 point cloud denoising method based on joint bilateral filtering and sharp feature skeleton extraction, which comprises the steps of 1) acquiring candidate feature points by using a normal vector difference method; 2) extracting a skeleton of the candidate points; 3) performing resampling on the candidate points by using the skeleton so as to acquire feature points; 4) endowing each feature point with a multi-normal vector; filtering a point cloud normal vector based on joint bilateral filtering framework; and 6) updating the point position based on the filtered normal vector to acquire a denoised point cloud model. According to the point cloud denoising method, a sharp feature skeleton is firstly extracted to perform analysis on the model structure, so that sharp features of an object are well maintained while denoising is performed, thereby being conducive to dealing with high-intensity noise. The point cloud denoising method has the characteristic of high robustness and has excellent popularization and application prospects.

Description

technical field [0001] The invention relates to the fields of computer graphics and three-dimensional point cloud denoising, in particular to a point cloud denoising method based on joint bilateral filtering and sharp feature skeleton extraction. Background technique [0002] Most of the 3D model data captured by 3D sensors are saved in point cloud format. Due to the limitation of the accuracy of scanning equipment, such as Microsoft Kinect, the captured point cloud data inevitably contains certain noise. Therefore, point cloud denoising plays a very fundamental and important role in the field of 3D geometry processing. The main challenge of point cloud denoising is how to preserve the detailed features of objects, especially sharp features, while denoising. [0003] Joint bilateral filtering, as an extension of the bilateral filtering technique, has been proven to be an effective feature-preserving method in the field of image processing. This technique has also been suc...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T2207/20028G06T5/70
Inventor 郑颖龙李桂清伍世浩
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com