Document Type
Article
Keywords
Big Data, Cartoon Generation, Video Processing, Agent-Based Interactions, Image Manipulation
Abstract
This study presents a novel method for animating videos using three Kaggle cartoon faces data sets. Dynamic interactions between cartoon agents and random backgrounds, as well as Gaussian blur, rotation, and noise addition, make cartoon visuals look better. This approach also evaluates video quality and animation design by calculating the backdrop colour's average and standard deviation, ensuring visually appealing material. This technology uses massive datasets to generate attractive animated videos for entertainment, teaching, and marketing.
How to Cite This Article
Mohialden, Yasmin Makki; khorsheed, Abbas Akram; and Hussien, Nadia Mahmood
(2024)
"Agent-Interacted Big Data-Driven Dynamic Cartoon Video Generator,"
Mesopotamian Journal of Big Data: Vol. 4:
Iss.
1, Article 4.
DOI: 10.58496/MJBD/2024/004
Available at:
https://map.researchcommons.org/mjbd/vol4/iss1/4