Neuro-Fuzzy Logic for Automatic Animation Scene Generation in Movie Arts in Digital Media Technology

Abstract

Abstract Animation scene generation (ASG) is the best digital media tool for lifelike scenes, particularly for movies. Traditional animation methods are laborious, computationally intensive, and scalable. Thus, this work addresses animation production issues using NFL-ASG. Combining fuzzy logic with a convolution neural network may create more realistic animated situations with less human interaction and better learning. Convolutional model training uses animation scenarios’ complicated motion patterns, character interactions, and ambient factors. Deep learning and fuzzy logic might change animation by boosting production techniques and releasing digital media technological creativity. After testing the system on the Moana Island scene dataset, it achieved a perception analysis success rate of 0.981% and a minimal processing complexity of (n logn).

Keywords

• Animation scene generation
• Convolution neural networks
• Fuzzy logic
• Moana island scene
• Computation complexity