Yurtsever, Mehmet AtaDidyk, PiotrChristie, MarcHan, Ping-HsuanLin, Shih-SyunPietroni, NicoSchneider, TeseoTsai, Hsin-RueyWang, Yu-ShuenZhang, Eugene2025-10-072025-10-072025978-3-03868-295-0https://doi.org/10.2312/pg.20251282https://diglib.eg.org/handle/10.2312/pg202512823D printing is widely used for prototyping and fabricating custom designs. Due to the discretization introduced during printing, the quality of the fabricated surfaces often suffers from so-called staircasing artifacts. While all 3D printers produce these artifacts, their severity depends on the printing resolution. Thus, these artifacts are particularly pronounced in low- to medium-cost printers, which are commonly used by home users, hobbyists, and enthusiasts of 3D printing. Changing the printing orientation allows for reducing the artifacts, enabling more accurate surface reproduction. While several previous works exploited this idea, they formulated the problem based on the geometrical accuracy of surface reproduction. This paper takes a different approach that focuses on the perception of the surface appearance. Our work is motivated by the fact that the visual severity of the artifacts depends on the characteristics of the patterns that the staircasing produces. These are also influenced by the viewing conditions, i.e., lighting and viewing orientations. Consequently, we develop in this paper a perception-inspired technique for quantifying the visibility of staircasing artifacts that takes the above factors into consideration. It is grounded in the human contrast sensitivity function, which models the ability of the human visual system to detect spatial patterns. Using the method, we propose an optimization procedure for finding the printing orientation for 3D models, which minimizes the visibility of staircasing artifacts. We evaluate our method against geometric approaches across a range of 3D models and viewing conditions. Our user study confirms the effectiveness of our approach in reducing the visual impact of staircasing artifacts.Attribution 4.0 International LicenseCCS Concepts: Computing methodologies → Shape analysis; Mesh models; PerceptionComputing methodologies → Shape analysisMesh modelsPerception10.2312/pg.202512829 pages