Abstract
Digital photogrammetry and spectral imaging are widely used in heritage sciences towards the comprehensive recording, understanding, and protection of historical artifacts and artworks. The availability of consumer-grade modified cameras for spectral acquisition, as an alternative to expensive multispectral sensors and multi-sensor apparatuses, along with semi-automatic software implementations of Structure-from-Motion (SfM) and Multiple-View-Stereo (MVS) algorithms, has made more feasible than ever the combination of those techniques. In the research presented here, the authors assess image-based modeling from near-infrared (NIR) imagery acquired with modified consumer-grade cameras, with applications on tangible heritage. Three-dimensional (3D) meshes, textured with the non-visible data, are produced and evaluated. Specifically, metric evaluations are conducted through extensive comparisons with models produced with image-based modeling from visible (VIS) imagery and with structured light scanning, to check the accuracy of results. Furthermore, the authors observe and discuss, how the implemented NIR modeling approach, affects the surface of the reconstructed models, and may counteract specific problems which arise from lighting conditions during VIS acquisition. The radiometric properties of the produced results are evaluated, in comparison to the respective results in the visible spectrum, on the capacity to enhance observation towards the characterization of the surface and under-surface state of preservation, and consequently, to support conservation interventions.
Highlights
Multi‐view image recording In the course of the last decade, rapid advancements in passive sensors for 3D recording, workflows for swift data acquisition, automatic or semi-automatic software which implement image-based reconstruction algorithmic approaches and computational systems for processing of large datasets, have taken place
Research aims In this work, we evaluate the use of imagery from consumer-grade digital reflex cameras modified for near-infrared imaging, in combination with image-based 3D reconstruction techniques, to produce high-fidelity models of tangible heritage assets textured with spectral information
The Ground-Sampling Distances (GSDs) that we present in Table 1 refer to an approximate average of the size of the pixel on each object, which was calculated inside the SfM/MVS based software
Summary
Multi‐view image recording In the course of the last decade, rapid advancements in passive sensors for 3D recording, workflows for swift data acquisition, automatic or semi-automatic software which implement image-based reconstruction algorithmic approaches and computational systems for processing of large datasets, have taken place. The use of 3D image-based modeling technologies has become common for various aspects of heritage science. Follows a Structurefrom-Motion (SfM) implementation to determine camera positions in 3D space and the coordinates of the scene, producing a sparse point cloud. Dense image matching algorithms enable further densification of the point cloud, as almost every pixel of the scene is reconstructed in 3D -a procedure typically named Multiple-View-Stereo (MVS) or dense stereo-matching. Later, these dense point clouds can be transformed into textured models via surfacing algorithms and texture mapping
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