NPF-Visual-Stability

Node–Path–Field Model for Visual Stability Analysis

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Overview

NPF-Visual-Stability is a research-oriented project that introduces the Node–Path–Field (NPF) model, a structural framework for analyzing and predicting visual stability in complex visual systems.

The model conceptualizes visual perception as the interaction of three structural components:

• Node — Local convergence points of visual attention
• Path — Directed transitions guiding attentional flow between nodes
• Field — Continuous distribution of global visual energy

Together, these elements describe how attention organizes itself within an image and how stable perceptual structures emerge.

The NPF model aims to provide a theoretical and computational foundation for analyzing visual stability across multiple domains, including:

• visual perception research
• image composition analysis
• artwork structure analysis
• interface and layout design
• computational aesthetics

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Conceptual Model

The conceptual structure of the Node–Path–Field model is illustrated below.

Figure 1. Conceptual representation of the Node–Path–Field model.

• Nodes (red circles) represent local convergence points of visual attention.
• Paths (blue arrows) represent directional attention transitions between nodes.
• Field (background gradient) represents the global distribution of visual energy across the image.

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Theoretical Framework

The Node–Path–Field model can be described conceptually through three interacting layers.

Node Layer

Set of attention convergence points: $$N = {n_1, n_2, \dots, n_k}$$

Each node represents a visually salient region within the image.

Path Layer

Directed attentional transitions between nodes: $$P = {(n_i \to n_j, w_{ij})}$$

where wij represents the transition weight between nodes.

Field Layer

Continuous global visual energy distribution: $$F(x,y) = \sum \phi_i(x,y)$$

where φi represents the influence function of node ni.

Together, these components form the NPF structural model of visual stability.

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Repository Structure

NPF-Visual-Stability │ ├── README.md └── model-diagram.png

Future updates may include:

• formal mathematical descriptions
• computational simulations
• experimental validation datasets
• example analyses

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Research Status

This repository currently presents the conceptual framework of the Node–Path–Field model.

Future work may explore:

• computational implementation of the NPF model
• quantitative metrics of visual stability
• integration with eye-tracking data
• applications in image analysis and visual design

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Citation

If you use or reference this work in academic research, please cite:

Pan, Y. (2026).
NPF-Visual-Stability: Node–Path–Field Model for Visual Stability Analysis.
GitHub Repository.

(A future arXiv or journal publication may be released.)

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Copyright

Copyright (c) 2026 Pan Yao

All rights reserved.

All algorithms, conceptual frameworks, diagrams, and written materials contained in this repository are the intellectual property of the author.

Unauthorized reproduction, redistribution, modification, or commercial use of any part of this project is strictly prohibited without explicit written permission from the copyright holder.

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Contact

For academic collaboration or research inquiries:

Pan Yao
Email: kelierpan5@gmail.com