Production Efficiency of 2D Pixel Art Through 3D Model Transformation Using Node-Based Compositing

Abstract

The game development industry demands high efficiency in visual asset production without compromising aesthetics. While 2D pixel art maintains consistent market appeal, its conventional manual frame-by-frame method is structurally limited in terms of consistency and scalability. This research designs and validates a deterministic hybrid pipeline for 3D-to-2D pixel art character asset production using Blender's Compositing Node, employing a Research and Development (R&D) approach combined with experimental methods. The pipeline integrates Rasterization Algorithms, Grid Snapping, and Downsampling Theory, with production time, visual quality, and reusability were evaluated objectively using screen-recording analysis. Three key findings were obtained. First, the pixel conversion formula Value = Render Resolution ÷ Target Resolution was mathematically validated across five resolution scenarios, yielding perfect matrix partitions without pixel residue; in the critical case (1080 px → 64 px), spatial deviation was only 0.74%, well below the industry tolerance threshold of 5–10%. Second, the pipeline achieved a Break-Even Point (BEP) at n ≈ 0.97, indicating that the reusable component investment (3.21 hours) was recovered before the first character was completed, with efficiency gains growing from 1.66% (1 asset) to 49.73% (10 assets). Third, the identified visual deviation of 1–2 pixels (1.56%–3.13%) falls below the Just Noticeable Difference (JND) threshold of 5–10%, confirming that pixel art aesthetics including outline sharpness, inter-frame proportional consistency, and silhouette readability remain fully intact. These results demonstrate that the proposed pipeline offers a reproducible, scalable, and AI-independent solution for mass production of pixel art character assets.