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Multimedia Character Modeling Design and Modeling of Cartoon Animation Based on Bayesian Sequence Recommendation
Hao Wu1,2, Shi-Jiang Wen1,3, Jong-Hoon Yang1
1Department of Digital Image in Sangmyung University, Seoul 03015, Republic of Korea.
Computational Intelligence and Neuroscience
|February 14, 2022
Summary
This study introduces a Bayesian sequence recommendation algorithm to enhance multimedia character design in cartoon animation. The method improves efficiency and supports the creation of characters aligning with positive values.
Area of Science:
- Computer Science
- Multimedia Arts
- Artificial Intelligence
Background:
- Multimedia and streaming media, including cartoon animation, are increasingly popular.
- There is a need for cartoon characters to align with mainstream values and convey positive energy.
- Existing character modeling processes can be inefficient.
Purpose of the Study:
- To develop a management framework for animation design documents.
- To provide a decision-making basis for efficient multimedia character creation.
- To improve the overall quality and efficiency of cartoon animation production.
Main Methods:
- Utilized a Bayesian sequence recommendation algorithm.
- Analyzed a three-tier architecture diagram for multimedia character modeling.
- Examined character modeling from hierarchy, behavior, and interactive process perspectives.
Main Results:
- Developed animation design management documents.
- Demonstrated the effectiveness of the Bayesian sequence recommendation algorithm.
- Showcased the algorithm's ability to support multimedia character design and modeling.
Conclusions:
- The Bayesian sequence recommendation algorithm is effective for multimedia character design.
- The proposed approach can accelerate the creation of cartoon animation characters.
- This method enhances the efficiency and quality of multimedia works.
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