Multimedia Human-Computer Interaction Method in Video Animation Based on Artificial Intelligence Technology

IF 0.6 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Linran Sun, Nojun Kwak
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引用次数: 0

Abstract

With the development of computer technology innovation, be able to deal with the media comprehensive information and real-time information interaction with the computer multimedia technology arises at the historic moment, it promotes the application fields of computer widen to industrial all aspects of life. As the product of digital technology, animation technology plays an irreplaceable role in the production of multimedia courseware. However, the existing human-computer interaction methods have shortcomings such as incomplete extraction of video features and poor human-computer interaction effect. In this context, this paper designs a multimedia human-computer interaction method for animation works based on CNN model. First of all, the original video data is collected and preprocessed. Then it is input into the HCI framework based on CNN model for feature extraction. Finally, the effectiveness and practicability of the proposed method are proved by simulation experiments, which provides a reference and basis for the research of modern human-computer interaction.
基于人工智能技术的视频动画中的多媒体人机交互方法
随着计算机技术的发展创新,能够处理媒体综合信息和实时信息交互的计算机多媒体技术应运而生,它推动着计算机的应用领域拓宽到产业生活的方方面面。动画技术作为数字技术的产物,在多媒体课件的制作中发挥着不可替代的作用。然而,现有的人机交互方法存在视频特征提取不完整、人机交互效果不佳等缺点。在此背景下,本文设计了一种基于 CNN 模型的动画作品多媒体人机交互方法。首先,采集原始视频数据并进行预处理。然后将其输入到基于 CNN 模型的人机交互框架中进行特征提取。最后,通过仿真实验证明了所提方法的有效性和实用性,为现代人机交互研究提供了参考和依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.60
自引率
0.00%
发文量
24
期刊介绍: Organizations are continuously overwhelmed by a variety of new information technologies, many are Web based. These new technologies are capitalizing on the widespread use of network and communication technologies for seamless integration of various issues in information and knowledge sharing within and among organizations. This emphasis on integrated approaches is unique to this journal and dictates cross platform and multidisciplinary strategy to research and practice.
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