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Three-dimensional human body motion analysis and synthesis method based on manifold learning

A technology of human motion and manifold learning, applied in image analysis, animation production, image data processing, etc., can solve problems such as impossible to meet the needs of animation, and achieve the effect of solving the disaster of dimensionality

Active Publication Date: 2012-06-27
DALIAN UNIV
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Problems solved by technology

For example, to establish impossible motion, since the original motion data retains the motion of the limbs in real motion, it is impossible to meet the animation needs of exaggerated expression, then analysis or synthesis technology is required

Method used

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  • Three-dimensional human body motion analysis and synthesis method based on manifold learning
  • Three-dimensional human body motion analysis and synthesis method based on manifold learning
  • Three-dimensional human body motion analysis and synthesis method based on manifold learning

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Embodiment Construction

[0027] The invention discloses a three-dimensional human motion analysis and synthesis method based on nonlinear dimension reduction. The method is based on the human body motion data obtained by the optical human body motion capture device, and applies the nonlinear manifold learning algorithm to the three-dimensional human body motion analysis and synthesis method. The acquisition frequency of optical motion capture equipment is high, and the obtained motion data is not only large in data volume and high in dimension, but also aiming at the nonlinear and global characteristics of human motion data, the nonlinear manifold learning algorithm and the synthesis method based on motion graph Combine. First, before composing the image, the method uses a nonlinear manifold dimensionality reduction method to map the high-dimensional motion samples onto the low-dimensional manifold, and after detailed analysis using the laws and characteristics presented on the low-dimensional curve, ...

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Abstract

The invention discloses a three-dimensional human body motion analysis and synthesis method based on manifold learning, which is characterized by comprising the following steps: 1) obtaining a human body attitude parameter sequence; 2) extracting required data from the human body attitude parameter; 3) reducing the dimension of the extracted motion information with a non-linear isometric mapping algorithm; 4) building the low-dimensional embedded curve model of each section of motion sequence; 5) storing a basic motion segment obtained by splitting; 6) converting a motion data format; 7) taking the basic motion segment obtained in the above step as a basic unit to calculate the similar frame of the motion segment, determining the distance parameter of the similar frame, and screening an optimal value; and 8) obtaining a new synthesis path according to an obtained motion diagram. With the method, the dimension disaster problem of the human body motion data is effectively solved, and a calculated amount problem in the later-stage motion diagram construction is effectively solved.

Description

technical field [0001] The invention relates to a method for analyzing and synthesizing three-dimensional human motion data, in particular to a method for analyzing and synthesizing three-dimensional human motion based on manifold learning. Background technique [0002] With the rapid development of computer software, hardware and graphics, 3D animation has also become a common media type. Nowadays, animations produced with computer technology as the carrier have received more and more attention in the fields of film and television production, games, simulation and sports training. Among them, human body animation, as the main part of 3D animation, has become a research field because it contains many degrees of freedom. points and difficulties. According to different methods of generating animation, currently commonly used computer animation techniques can be divided into method based on program, method based on physics, method based on video and method based on motion capt...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/20G06T13/20
Inventor 张强刘燕燕魏小鹏
Owner DALIAN UNIV
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