An Automated Generation from Video to 3D Character Animation using Artificial Intelligence and Pose Estimate

IF 1.7 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal Pub Date : 2023-04-29 DOI:10.5121/csit.2023.130703
Daniel Haocheng Xian, Jonathan Sahagun
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引用次数: 1

Abstract

This paper presents a novel approach to automatically generate 3D character animation from video using artificial intelligence and pose estimation [3]. The proposed system first extracts the pose information fromthe input videousing a pose estimation model [2]. Then, an artificial neural network is trained to generate the corresponding3Dcharacter animation based on the extracted pose information [1]. The generated animation is then refined usingaset of animation filters to enhance the quality of the final output. Our experimental results demonstrate theef ectiveness of the proposed approach in generating realistic and natural-looking 3D character animations fromvideo input [4]. This automated process has the potential to greatly reduce the time and ef ort required for creating3D character animations, making it a valuable tool for the entertainment and gaming industries.
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使用人工智能和姿态估计从视频到3D角色动画的自动生成
本文提出了一种利用人工智能和姿态估计从视频中自动生成3D角色动画的新方法[3]。该系统首先利用姿态估计模型从输入视频中提取姿态信息[2]。然后,基于提取的姿态信息,训练人工神经网络生成相应的3d角色动画[1]。生成的动画然后使用一组动画过滤器来提高最终输出的质量。我们的实验结果证明了该方法在从视频输入生成逼真和自然的3D角色动画方面的有效性[4]。这种自动化过程有可能大大减少创建3d角色动画所需的时间和精力,使其成为娱乐和游戏行业的宝贵工具。
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来源期刊
CiteScore
1.40
自引率
0.00%
发文量
22
审稿时长
4 weeks
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