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
{"title":"An Automated Generation from Video to 3D Character Animation using Artificial Intelligence and Pose Estimate","authors":"Daniel Haocheng Xian, Jonathan Sahagun","doi":"10.5121/csit.2023.130703","DOIUrl":null,"url":null,"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.","PeriodicalId":42597,"journal":{"name":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","volume":"14 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/csit.2023.130703","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
1.40
自引率
0.00%
发文量
22
审稿时长
4 weeks
期刊最新文献
Enhancing Energy Efficiency in Cluster Based WSN using Grey Wolf Optimization Comparison of Pre-trained vs Custom-trained Word Embedding Models for Word Sense Disambiguation Healthcare Data Collection Using Internet of Things and Blockchain Based Decentralized Data Storage Development of an Extended Medical Diagnostic System for Typhoid and Malaria Fever Comparison of Swarm-based Metaheuristic and Gradient Descent-based Algorithms in Artificial Neural Network Training
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1