Keywords: unity, occlusion Culling, static analysis, 3D scene rendering optimization, automation tools
UDC 004.925
DOI: 10.26102/2310-6018/2026.57.6.016
The paper considers the application of an adaptive object gradation method based on geometric complexity for automating the formation of a set of occluders in 3D scenes developed using graphics engines. The proposed approach involves classifying objects according to their level of geometric complexity and incorporating this characteristic into the decision-making process for their use as occluders. The method is implemented as an extension of an approach for occluder selection based on ray-object intersection analysis. A bounding volume hierarchy is used to accelerate the analysis. The approach assumes that an object is considered an occluder if the number of ray hits exceeds a predefined threshold. The proposed method extends this approach by introducing an adaptive threshold calculated based on the classification of objects according to the number of triangles they contain. Experimental evaluation was performed in the Unity engine using two 3D scenes populated with basic primitives and low-poly models in different quantities. For simple scenes, the difference between the base and adaptive thresholds is insignificant; however, in more complex cases, the method allows narrowing the set of selected occluders. The results demonstrate that the method provides a more selective classification of occluders in scenes with high object density and highlights the importance of additional factors, including object size and spatial distribution.
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Keywords: unity, occlusion Culling, static analysis, 3D scene rendering optimization, automation tools
For citation: Chernyi V.G., Bolsunovskaya M.V. Adaptive object gradation method for occlusion culling configuration. Modeling, Optimization and Information Technology. 2026;14(6). URL: https://moitvivt.ru/ru/journal/article?id=2303 DOI: 10.26102/2310-6018/2026.57.6.016 (In Russ).
© Chernyi V.G., Bolsunovskaya M.V. Статья опубликована на условиях лицензии Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NS 4.0)Received 05.04.2026
Revised 16.06.2026
Accepted 26.06.2026
Published 30.06.2026