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

Method of employing improved k-means to perform spatial domain segmentation on three-dimensional model

An airspace segmentation and three-dimensional model technology, which is applied in the multimedia field and can solve the problems of different initial value results, large dependence of initial value selection, and local minimum solution of the algorithm.

Active Publication Date: 2016-05-18
ZHEJIANG GONGSHANG UNIVERSITY
View PDF1 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But this algorithm has its inherent shortcomings. First, k in the algorithm is given in advance, and the selection of the value of k is difficult to estimate, because in most cases, it is not known how much a given data set should be divided into Secondly, the algorithm is very dependent on the selection of the initial value, and the algorithm often falls into a local minimum solution, and the results of different initial values ​​are often different; finally, the algorithm needs to continuously adjust the sample classification and continuously calculate and adjust After the new cluster center, so when the amount of data is very large, the time overhead of the algorithm is also very large

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 of employing improved k-means to perform spatial domain segmentation on three-dimensional model
  • Method of employing improved k-means to perform spatial domain segmentation on three-dimensional model
  • Method of employing improved k-means to perform spatial domain segmentation on three-dimensional model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0020] The present invention will be further described below.

[0021] The inventive method is specifically:

[0022] Step 1: Suppose the number of frames is F, and the number of vertices contained in each frame is N, F>0, N>0. Connect the coordinates of the vertices whose curvature is to be calculated in all frames into a curve, and the curvature in a certain frame is the curvature of the corresponding point on the curve. Save the calculated curvature to the cell matrix k, where k=cell(1,N), k{i} is a row vector, and length(k{i})=F-2, 1≤i≤N. Find the curvature expectation of each vertex in all frames and store it in the matrix E and draw the curvature expectation graph, where E is a row vector, and length(E)=N:

[0023] E ( i ) = Σ j = 1 : F ...

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 of employing improved k-means to perform spatial domain segmentation on a three-dimensional model, comprising: first connecting the coordinates of vertexes of a curvature to be solved in all frames into a curve and employing a spectral analysis method to segment a target model; initially classifying the vertexes into blocks according to a vertex curvature expectation, i.e., classifying vertex with a same vertex curvature expectation into a block; respectively calculating the metric d between other vertexes and s vertexes; updating the center of each cluster, i.e., according to the expectation of all vertex metrics in each part, finding the vertex metric in the part which is proximate to the expectation to be used as a new clustering center of the part; and finally repeating until a threshold is smaller than a set value. The method employs a curvature to represent model motion intensity, and creatively defines the weighted mean between a Euclidean distance and a curvature expectation as a clustering metric; the clustering result guarantees space continuity as well as model motility.

Description

technical field [0001] The invention belongs to the multimedia technical field of three-dimensional animation model compression, and in particular relates to an improved k-means airspace segmentation method. Background technique [0002] With the continuous enrichment of 3D data acquisition methods, the maturity of computer graphics-related theories and technologies, and the rapid development of network technology, 3D models, as the fifth multimedia data type after text, audio, image (graphics) and video, are becoming more and more popular. Industrial manufacturing, product display, architectural design, robotics, medicine, e-commerce, education and training, military simulation, film and television entertainment and many other fields play an increasingly important role and give full play to its unique advantages. [0003] However, while increasingly sophisticated and perfect 3D models are widely used, the surge in data volume and complexity has brought great challenges to t...

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): G06T7/00
CPCG06T2207/10012
Inventor 杨柏林宋超张露红张勋
Owner ZHEJIANG GONGSHANG UNIVERSITY
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