Real-Time Image Animation Using AI Machine Learning and Deep Learning

Augmented Reality (AR) and Artificial Intelligence (AI)-driven animation are revolutionizing maintenance operations by enabling real-time, interactive guidance. Traditional methods, such as FARA [1], have introduced geometry-based AR authoring approaches for maintenance tasks. However, this paper presents a novel deep learning-based animation system that automates the synthesis of facial expressions and object motions, enhancing AR-assisted maintenance processes. By leveraging AI-driven motion analysis, the proposed system streamlines maintenance workflows, improves precision, and reduces human intervention in animation creation. The integration of deep learning techniques ensures adaptive and responsive animation sequences, optimizing operational efficiency and user experience in maintenance environments. This approach represents a significant advancement in AR-guided repair and maintenance, setting the foundation for future intelligent maintenance solutions.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-04-26
DOI
https://doi.org/10.52783/jisem.v10i40s.7581
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

Real-Time Image Animation Using AI Machine Learning and Deep Learning

S. S. Ripote
Journal of Information Systems Engineering & Management
Human Motion and Animation
article

Real-Time Image Animation Using AI Machine Learning and Deep Learning

S. S. Ripote
article en

Abstract

Augmented Reality (AR) and Artificial Intelligence (AI)-driven animation are revolutionizing maintenance operations by enabling real-time, interactive guidance. Traditional methods, such as FARA [1], have introduced geometry-based AR authoring approaches for maintenance tasks. However, this paper presents a novel deep learning-based animation system that automates the synthesis of facial expressions and object motions, enhancing AR-assisted maintenance processes. By leveraging AI-driven motion analysis, the proposed system streamlines maintenance workflows, improves precision, and reduces human intervention in animation creation. The integration of deep learning techniques ensures adaptive and responsive animation sequences, optimizing operational efficiency and user experience in maintenance environments. This approach represents a significant advancement in AR-guided repair and maintenance, setting the foundation for future intelligent maintenance solutions.

Journal of Information Systems Engineering & ManagementVol. 10(40s)
Openalex Percentile: Top 90%
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.

Real-Time Image Animation Using AI Machine Learning and Deep Learning — S. S. Ripote · Journal of Information Systems Engineering & Management (2025) | TGRS Research Map | TGRS