Interpretable Multi-Criteria Evaluation for Detecting Key Points on 3D Surfaces
Abstract
Interpretable Multi-Criteria Evaluation for Detecting Key Points on 3D Surfaces
Incoming article date: 06.12.2025The study addresses the problem of identifying key points on three-dimensional surfaces of physical objects that are required for placement or fixation of elements in engineering and medical applications. Direct determination of such points on real objects is limited by restricted access, geometric variability, and high accuracy requirements; therefore, digital 3D models incorporating both external and internal structure are used as the basis for analysis. An interpretable multi-criteria suitability evaluation approach is proposed, based on fuzzy logic inference, enabling integration of strict constraints and preferential criteria originating from different subject domains. The methodological framework combines systematic literature analysis, expert knowledge integration, and mathematical formalization of multi-criteria decision making. Particular attention is given to explainability and transferability, which are critical for medical scenarios (anatomical landmarks) as well as engineering and robotics scenarios (geometric and technological landmarks). The developed model generates suitability heatmaps and automatically identifies a set of admissible points that is consistent with expert annotations and safety requirements.
Keywords: key point detection; fuzzy logic inference; decision support expert system