Connected Semantic Concepts as a Base for Optimal Recording and Computer-Based Modelling of Cultural

January 2019
Conference: Structural Analysis of Historical Constructions
Project: Knowledge based Object Detection in Images and Point Clouds
Lab: Frank Boochs’s Lab

Presentation of the part of terrace house 2 representing mill B17:
(a) Point cloud with watermill room 1 in yellow.
(b) Ground plot of the watermill including the schematic geometric descriptions.

Abstract and figures

3D and spectral digital recording of cultural heritage monuments is a common activity for their documentation, preservation, conservation management, and reconstruction. Recent developments in 3D and spectral technologies have provided enough flexibility in selecting one technology over another, depending on the data content and quality demands of the data application. Each technology has its own pros/cons, suited perfectly to some situations and not to others. They are mostly unknown to humanities experts, besides having a limited understanding of the data requirements demanded by the research question. These are often left to technical experts who again have a limited understanding of cultural heritage requirements. A common point of view has to be achieved through interdisciplinary discussions. Such agreements need to be documented for their future references and re-uses. We present a method based on semantic concepts that not only documents the semantic essence of such discussions, but also uses it to infer a guidance mechanism that recommends technologies/technical process to generate the required data based on individual needs. Experts’ knowledge is represented explicitly through a knowledge representation that allows machines to manage and infer recommendations. First, descriptive semantics guide end users to select the optimal technology/technologies for recording data. Second, structured knowledge controls the processing chain extracting and classifying objects contained in the acquired data. Circumstantial situations during object recording and the behaviour of the technologies in that situation are taken into account. We will explain the approach as such and give results from tests at a CH object.

Chronological results of:
(a) floor, building wall and their parts classification according to their topological relation;
(b) room recognition;
(c) watermill recognition.
Thanks to the good detection of a room, the semantic classification identifies the watermill using the features provided by the data description.

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