This paper presents an experimental analysis of the behavior of a significance metric for 3D scene objects used for preliminary rendering optimization setup in the Unity environment. The influence of three object characteristics is considered, from which the final significance metric is formed: geometric complexity (polygon count), spatial size, and the object’s potential as an occluder, calculated based on visibility analysis performed using ray casting. Combining these features with adjustable weights makes it possible to obtain a unified estimate of the potential importance of an object and its impact on rendering during the configuration of optimization approaches. The results show that geometric complexity provides strong separation of objects into groups, assigning 22.6% of the objects in the experimental scene to the high-significance category. The balanced configuration and the dominance of other coefficients individually demonstrate lower differentiation, yet accurately identify the most complex objects intentionally placed in the scene, while classifying over 70% of the remaining models as low-significance. Regardless of the chosen configuration, the method correctly identifies candidates clearly suitable for further optimization.
Chernyi et al. (Fri,) studied this question.