Three-dimensional (3D) digitization has become a central methodological pillar in cultural heritage documentation, conservation support, and dissemination. Despite the maturity of image-based photogrammetry and active sensing technologies, real-world digitization campaigns frequently diverge from idealized workflows due to constraints related to object accessibility, surface properties, lighting conditions, and operational feasibility. As a result, practitioners are often required to adapt acquisition and processing strategies dynamically, balancing geometric fidelity, visual quality, and practical limitations. This study presents a practice-oriented analysis of applied digitization workflows conducted in controlled indoor and museum environments, focusing on fragile and optically challenging cultural and paleontological objects. Structured light scanning, DSLR-based photogrammetry, and hybrid approaches were systematically explored. While structured light scanning offered high nominal resolution, its performance proved sensitive to material properties and surface behavior, leading to incomplete or unstable reconstructions in several cases. Photogrammetric workflows, when supported by controlled acquisition setups, yielded robust and visually coherent results for the majority of objects. For cases where conventional photogrammetry underperformed, alternative AI-assisted image-based reconstruction pipelines were evaluated as complementary solutions. Rather than emphasizing only successful outcomes, the paper documents recurring failure modes, decision-making trade-offs, and breakdown points across acquisition, alignment, meshing, and texturing stages. Empirical observations are synthesized into qualitative comparisons and decision-support tables, highlighting the conditions under which specific digitization strategies succeed or fail. The findings underscore that hybrid workflows, while theoretically advantageous, can amplify integration complexity and error propagation if not carefully constrained. By foregrounding practical constraints and adaptive methodological choices, this work contributes a transparent, experience-driven perspective on cultural heritage digitization, supporting more resilient planning and informed decision-making in future documentation and conservation projects.
Iakovaki et al. (2026) studied this question.