This article demonstrates an efficient method to analyze 3D point clouds in cultural heritage, implying broader applications.
In this article, we propose a method for analysing 3D point clouds. To this aim, we take advantage of the octree data structure to compress and analyse the 3D point data. The motivation for the study undertaken comes from the field of Cultural Heritage. As 3D acquisition methods become more and more ubiquitous in this field, there is an increasing need for methods, which help to efficiently store, display, and share large data sets. There is also a need to segment and classify the recorded data. We show that the octree data structure provides an efficient tool for handling complex 3D data, coming from different applications. Although we tested our method on a data set, coming from the field of archaeology, based on photogrammetric method, we believe that the approach proposed has much wider use. The method proposed can be applied to any 3D data, represented in a given coordinate system.
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Bieńkowski et al. (2025) studied this question.
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