The Classification System of an Artificial Intelligence Animation through Taxonomy

This study proposed a classification of emerging artificial intelligence animations based on the latest technology. A method of understanding the status of artificial intelligence animation in animation was systematized by using a taxonomic hierarchy categorized. Therefore the hierarchical structure of library science's document classification system was used as an example. A theoretical basis was also established through Lev Manovich of media studies. The research methodology used qualitative research methods to present theoretical background and case analysis was conducted using quantitative research methods. The subject of the case is artificial intelligence animation produced between 2023 and 2024. The selection method was to select five works from 2024 in reverse chronological order of production time. As a result of the study, the classification of artificial intelligence animation in animation was found to be L0 Animation(A) and then, L1 digital animation (L1-D·A). The L2 was computer-generated image animation (L2-CGI·A), and the final L3 was AI animation (L3-AI·A). Thus, in this paper, AI animation was newly identified from the animation perspective. In future research, I planning to conduct research on the cultural content of AI animation based on the results of this paper.

Authors

Publication Details

Journal
Journal of Korea Multimedia Society
Published
2024-12-31
DOI
https://doi.org/10.9717/kmms.2024.27.12.1515
Primary Topic
Human Motion and Animation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Classification System of an Artificial Intelligence Animation through Taxonomy

Ming Yang, Myeong-Sam Kim
Journal of Korea Multimedia Society
Human Motion and Animation
article

The Classification System of an Artificial Intelligence Animation through Taxonomy

Ming Yang, Myeong-Sam Kim
article en

Abstract

This study proposed a classification of emerging artificial intelligence animations based on the latest technology. A method of understanding the status of artificial intelligence animation in animation was systematized by using a taxonomic hierarchy categorized. Therefore the hierarchical structure of library science's document classification system was used as an example. A theoretical basis was also established through Lev Manovich of media studies. The research methodology used qualitative research methods to present theoretical background and case analysis was conducted using quantitative research methods. The subject of the case is artificial intelligence animation produced between 2023 and 2024. The selection method was to select five works from 2024 in reverse chronological order of production time. As a result of the study, the classification of artificial intelligence animation in animation was found to be L0 Animation(A) and then, L1 digital animation (L1-D·A). The L2 was computer-generated image animation (L2-CGI·A), and the final L3 was AI animation (L3-AI·A). Thus, in this paper, AI animation was newly identified from the animation perspective. In future research, I planning to conduct research on the cultural content of AI animation based on the results of this paper.

Journal of Korea Multimedia SocietyVol. 27(12)
Openalex Percentile: Top 68%
Human Motion and Animation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.