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Selection method of transition point of motion diagram based on non-linear manifold learning

A popular learning and motion graphics technology, applied in animation production, image data processing, instruments, etc., can solve the problems of high time complexity and inaccurate selection of jump points

Inactive Publication Date: 2015-05-27
DALIAN YOUJIA SOFTWARE TECH
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Problems solved by technology

[0006] In view of the above problems, the present invention develops a motion map transition point selection method based on nonlinear popular learning. The method focuses on solving the problem of jump point selection time in the motion map construction process by establishing and calculating the similarity between key motion data segments. The problem of high complexity and inaccurate selection can improve the construction efficiency of the motion map and make the generated motion data smoother and more natural

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  • Selection method of transition point of motion diagram based on non-linear manifold learning
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  • Selection method of transition point of motion diagram based on non-linear manifold learning

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Embodiment Construction

[0025] Below in conjunction with accompanying drawing, the present invention is further explained, and an embodiment of the unit of the present invention is:

[0026] The embodiments of the present invention are implemented on the premise of the technical solutions of the present invention, and detailed implementation methods and specific operation processes are given, but the protection scope of the present invention is not limited to the following embodiments.

[0027] Such as figure 1 Shown is the algorithm flow chart of the present invention, and it specifically comprises the following technical links:

[0028] Step 1: Dimensionality reduction analysis of high-dimensional data

[0029] Use the ISOMAP nonlinear manifold learning algorithm to reduce the dimensionality of high-dimensional human motion data to obtain the low-dimensional manifold structure of the original motion sequence, and draw the matching low-dimensional characteristic curve according to the different ty...

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Abstract

The invention discloses a selection method of a transition point of a motion diagram based on non-linear manifold learning, and belongs to the technical field of computer image processing. The method comprises the steps of performing dimensionality reduction analysis of high dimensional data, extracting key data segments, computing interframe similarity of the key data segments, and constructing the motion diagram.

Description

technical field [0001] The invention relates to a method for selecting a transition point of a motion map based on nonlinear popular learning, and belongs to the technical field of computer image processing. Background technique [0002] In recent years, with the advancement of computer software and hardware technology, computer animation technology has developed rapidly. Computer animation refers to the use of graphics and image processing technology, based on solid modeling and realistic display technology, with the help of programming or animation production The software generates a series of scene pictures. It involves many fields such as image processing technology, motion control principle, video technology and art, and has gradually become a comprehensive field of various disciplines and technologies with its unique characteristics. Among them, with the continuous development of motion capture technology, people can use the data captured by capture devices to generat...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T13/40
CPCG06T13/40
Inventor 盖丽
Owner DALIAN YOUJIA SOFTWARE TECH
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