The Effect of Characters’ Locomotion on Audience Perception of Crowd Animation

Wen-yu, Zhang; Adamo-Villani, Nicoletta

doi:10.1007/978-3-030-95531-1_27

Cited by 1 publication

(1 citation statement)

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“…At present, the mass animation production method has been widely used in many commercial movies, and commercial software specially used for mass animation production has been produced, such as the famous large-scale mass animation software, which created amazing animations in the movie " e Lord of the Rings," and visual e ects and won the 2003 Academy Award for Science and Engineering. In addition to lm and television e ects, crowd animation is widely used in the eld of game entertainment and simulation research, so crowd animation has profound research signi cance [1][2][3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

An Animation Model Generation Method Based on Gaussian Mutation Genetic Algorithm to Optimize Neural Network

Liu

Chen

Zhang

et al. 2022

Computational Intelligence and Neuroscience

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With the rapid development of computer graphics, 3D animation has been applied to all fields of people’s lives, especially in the industries of film and television works, games, and entertainment. The wide application of animation technology makes it difficult for general 3D animation effects to impress increasingly discerning audiences. Group animation, as a new focus, has received more and more attention and has become a hot issue in computer graphics. Traditional animation production mainly relies on manual drawing and key frame technologies. The limitations of these technologies make the production of group animation consume a lot of manpower, financial resources, and time, and cannot guarantee the intelligence of characters and the authenticity of group behavior. Therefore, in order to end the above issues, this paper proposes an animation model generation method based on Gaussian mutation genetic algorithm to optimize neural network, including obtaining animation scene data, according to the animation scene data, and extracting animation model elements. The elements are input into the model network, the target animation model is generated, and the target animation model is displayed. The method proposed in this paper improves the animation model generation method in the prior art to a certain extent. The proposed animation model is constructed only through fixed rules, and the composition rules of the model cannot be changed according to the historical data of the animation model construction and other factors. Technical issues that reduce the flexibility and accuracy of the animation model generation.

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