Neutrosophic Models for Stereo Depth, Scene Layers, and Confidence Estimation in 3D Animation Production Effect

Abstract

This paper presents three new mathematical models based on neutrosophic 
logic and topological structures to improve stereo effects in 3D animation. The first model 
uses NeutroTopology to represent depth with truth, indeterminacy, and falsehood values, 
instead of single numbers. This helps handle difficult areas like occlusion or semi
transparent objects. The second model applies SuperHyperTopology to divide a 3D scene 
into layers (such as foreground, background, etc.), treating each layer as a separate space 
with its own properties. This makes complex animations more accurate and easier to 
manage. The third model introduces Neutrosophic Probability Fusion to calculate how 
much we can trust depth data. It combines information from different sources (like stereo 
matching and motion) using a special rule that includes uncertainty. 
Each model is explained with equations and full examples. The results show better depth 
maps and more realistic 3D scenes, especially in areas that are normally hard to process.

DOI: 10.5281/zenodo.15926789