Edge sampling and edge binding method based on optimal transmission theory

An optimal and theoretical technology, applied in the field of edge sampling and edge bundling based on optimal transmission theory, it can solve problems such as inability to obtain information as a whole, confusion in the visualization method of node connection graphs, and inability to track edges, so as to achieve easy understanding. , the effect of solving visual confusion

Inactive Publication Date: 2020-06-09
CHONGQING UNIV OF POSTS & TELECOMM
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, as the scale of data increases day by day, the visualization method of node connection graph becomes chaotic, and serious visual confusion occurs. The information presented by the entire data set cannot be derived as a whole

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  • Edge sampling and edge binding method based on optimal transmission theory
  • Edge sampling and edge binding method based on optimal transmission theory
  • Edge sampling and edge binding method based on optimal transmission theory

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Embodiment Construction

[0054]Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic concept of the present invention, and the following embodiments and the features in the embodiments can be combined with each other in the case of no conflict.

[0055] Wherein, the accompanying drawings are for illustrative purposes only, and represent only schematic diagrams, rather than physical drawings, and should ...

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Abstract

The invention relates to an edge sampling and edge binding method based on an optimal transmission theory, and belongs to the field of graphics and visualization. The method comprises the following steps: S1, inputting a node connection graph, and clustering edges based on directions and distances by utilizing a hierarchical clustering algorithm and using different distance functions; S2, samplinga common edge from each type of edge set as a skeleton by using an optimal transmission theory; S3, respectively selecting end points and gravity center points of the edges as control points to drawtwo cubic Bezier curves, and connecting end points of the curves; S4, setting low transparency for the Bezier curve part, setting high transparency for the end point connecting line part, directly drawing short edges and setting extremely low transparency; and S5, measuring the excessive drawing number of each pixel, and further emphasizing binding by using an OpenGL rendering technology. The method has a good binding effect, the clustering number can be changed to control the binding tightness, and a user can recognize the main skeleton structure of the whole data set at a higher layer.

Description

technical field [0001] The invention belongs to the field of graphics and visualization, and relates to a side-sampling and side-binding method based on optimal transmission theory. Background technique [0002] Data visualization mainly uses graphical means to explain data, so that users can conduct in-depth observation and analysis of data. There are many visualization methods today, and different data types can use different visualization methods. Among the many visualized objects, the node connection graph is a basic and important structure. It is composed of vertices and edges and is suitable for representing entities and entities. The relationship between entities is represented by vertices, and the relationship between entities is represented by edges. The node connection graph is widely used, and many problems can be solved by establishing a node connection graph model, such as hierarchical structure and network structure. However, as the scale of data increases da...

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Application Information

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IPC IPC(8): G06T11/00G06T19/20G06F9/451G06K9/62
CPCG06T11/001G06T19/20G06F9/451G06F18/23
Inventor 秦红星周妩
Owner CHONGQING UNIV OF POSTS & TELECOMM
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