Scattered point cloud compression algorithm based on feature reservation

A compression algorithm and technology of scattered points, applied in electrical components, code conversion, etc., can solve the problems of difficulty in processing scattered point clouds, disorder of points and points, and unsatisfactory effects, achieving good compression effect and high reliability. reliability and efficiency

Inactive Publication Date: 2014-04-02
SHANGHAI MUNICIPAL ENG DESIGN INST GRP
View PDF3 Cites 33 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the processing of scattered point clouds is more difficult, and the points are disordered and irregular. The data compression method suitable for ordered point clouds cannot be directly used for disordered point cloud data, and the effect is not ideal.

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
  • Scattered point cloud compression algorithm based on feature reservation
  • Scattered point cloud compression algorithm based on feature reservation
  • Scattered point cloud compression algorithm based on feature reservation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0025] The present invention will be further described below in conjunction with accompanying drawings and examples.

[0026] 1 Method overview

[0027] The algorithm proposes a point cloud compression algorithm based on feature preservation for scattered point clouds, in order to achieve high efficiency while retaining features. Firstly, the point cloud segmentation technology is used to improve the search efficiency of the scattered point neighborhood, and the point normal vector, curvature, etc. are calculated, and the feature points are retained according to the simplification criterion. Finally, based on the octree theory, the grid is continuously refined until the minimum network If the grid meets the requirements, take a representative point in the smallest grid and delete other points. figure 2 The flowchart of the whole point cloud compression algorithm is given.

[0028] 2 Search of nearest neighbors

[0029] To compress data points, it is necessary to know the v...

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 scattered point cloud compression algorithm based on feature reservation. The scattered point cloud compression algorithm comprises the following steps: step 1, taking a point from a point set, utilizing a partitioning technology to search K neighborhood, and creating a point cloud topologic relation; step 2, according to the K neighborhood of the point, calculating normal vectors and curvature of the point cloud, and adjusting the normal vector directions to enable the normal vector directions to be consistent; step 3, according to the curvature, taking out feature points meeting the requirements and reserving the feature points; step 4, taking an octree theory as a basis, according to a simplification principle, in the premise of ensuring the object characteristics, simplifying the point cloud. The scattered point cloud compression algorithm has the advantages that the partitioning technology is utilized to improve the neighborhood search, and data simplification is completed on the basis of object feature reservation. The compression algorithm can be used for the fields such as mapping, computer graphics, and true three-dimensional model reconstruction, is high in reliability, good in compression effect, and wide in application prospect.

Description

technical field [0001] The present invention relates to a method for rapid registration of massive point cloud data in the fields of surveying and mapping, computational mathematics, computer graphics and visual technology, specifically a feature-preserving-based scattered point cloud compression algorithm, which can be used in virtual reality, digital cities, ancient It has important application value in the fields of building protection, point cloud data processing, and 3D reconstruction. Background technique [0002] In reverse engineering, general laser measurement equipment can easily obtain hundreds of thousands or even millions of high-density measurement data from the surface of the product. , generally do not need too dense data points, massive data not only makes the display and storage of data consume a lot of time and computer resources, increases the load on the system, but also greatly reduces the efficiency of subsequent processing. Therefore, the compression...

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): H03M7/30
Inventor 张鸿飞罗永权
Owner SHANGHAI MUNICIPAL ENG DESIGN INST GRP
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products