CultLab3D - On the Verge of 3D Mass Digitization

Santos, Pedro; Ritz, Martin; Tausch, Reimar; Schmedt, Hendrik; Monroy, Rafael; Stefano, A. De; Posniak, O.; Fuhrmann, Constanze; Fellner, Dieter W.

doi:10.2312/gch.20141305

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…We evaluated our compression algorithm on four multi-view geometry datasets acquired with the CultArm3D scanning station of the Competence Center Cultural Heritage Digitization of the Fraunhofer Institute for Computer Graphics Research [17,18,20]. These depict the Tin Cup (610 images), the Apple artifact (300 images) and the Mars Venus Amor dataset (1620 images) on the one hand.…”

Section: Datasets and Segmentation Resultsmentioning

confidence: 99%

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Depth-of-Field Segmentation for Near-lossless Image Compression and 3D Reconstruction

Buelow

Tausch

Schurig

et al. 2022

J. Comput. Cult. Herit.

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Over the years, photometric 3d reconstruction gained increasing importance in several disciplines, especially in cultural heritage preservation. While increasing sizes of images and datasets enhanced the overall reconstruction results, requirements in storage got immense. Additionally, unsharp areas in the background have a negative influence on 3d reconstructions algorithms. Handling the sharp foreground differently from the background simultaneously helps to reduce storage size requirements and improves 3d reconstruction results. In this paper, we examine regions outside the Depth of Field (DoF) and eliminate their inaccurate information to 3d reconstructions. We extract DoF maps from the images and use them to handle the foreground and background with different compression backends making sure that the actual object is compressed losslessly. Our algorithm achieves compression rates between 1:8 and 1:30 depending on the artifact and DoF size and improves the 3d reconstruction.

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Section: Datasets and Segmentation Resultsmentioning

confidence: 99%

“…Color-Based Masking. To automatically mask image sets of arbitrary size suited for photogrammetric 3d reconstruction the Competence Center For Cultural Heritage Digitization [17,18] of the Fraunhofer Institute for Computer Graphics Research developed an image masking application that requires only little initial user input.…”

Section: Image Maskingmentioning

confidence: 99%

Depth-of-Field Segmentation for Near-lossless Image Compression and 3D Reconstruction

Buelow

Tausch

Schurig

et al. 2022

J. Comput. Cult. Herit.

Self Cite

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Cross-Modal Search and Exploration of Greek Painted Pottery

Trinkl,

Karl,

Lengauer

et al. 2024

The 3 Dimensions of Digitalised Archaeology

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This paper focuses on digitally-supported research methods for an important group of cultural heritage objects, the Greek pottery, especially with figured decoration. The design, development and application of new digital methods for searching, comparing, and visually exploring these vases need an interdisciplinary approach to effectively analyse the various features of the vases, like shape, decoration, and manufacturing techniques, and relationships between the vases. We motivate the need and opportunities by a multimodal representation of the objects, including 3D shape, material, and painting. We then illustrate a range of innovative methods for these representations, including quantified surface and capacity comparison, material analysis, image flattening from 3D objects, retrieval and comparison of shapes and paintings, and multidimensional data visualization. We also discuss challenges and future work in this area.

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Optimal Lateral Displacement in Automatic Close-Range Photogrammetry

Guidi

Malik

Micoli

2020

Sensors

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Based on the use of automatic photogrammetry, different researchers made evident that the level of overlap between adjacent photographs directly affects the uncertainty of the 3D dense cloud originated by the Structure from Motion/Image Matching (SfM/IM) process. The purpose of this study was to investigate if, in the case of a convergent shooting typical of close-range photogrammetry, an optimal lateral displacement of the camera for minimizing the 3D data uncertainty could be identified. We examined five different test objects made of rock, differing in terms of stone type and visual appearance. First, an accurate reference data set was generated by acquiring each object with an active range device, based on pattern projection (σz = 18 µm). Then, each object was 3D-captured with photogrammetry, using a set of images taken radially, with the camera pointing to the center of the specimen. The camera–object minimum distance was kept at 200 mm during the shooting, and the angular displacement was as small as π/60. We generated several dense clouds by sampling the original redundant sequence at angular displacements (nπ/60, n=1, 2, … 8). Each 3D cloud was then compared with the reference, implementing an accurate scaling protocol to minimize systematic errors. The residual standard deviation of error made consistently evident a range of angular displacements among images that appear to be optimal for reducing the measurement uncertainty, independent of each specimen shape, material, and texture. Such a result provides guidance about how best to arrange the cameras’ geometry for 3D digitization of a stone cultural heritage artifact with several convergent shots. The photogrammetric tool used in the experiments was Agisoft Metashape.

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CultLab3D - On the Verge of 3D Mass Digitization

Cited by 4 publications

References 16 publications

Depth-of-Field Segmentation for Near-lossless Image Compression and 3D Reconstruction

Depth-of-Field Segmentation for Near-lossless Image Compression and 3D Reconstruction

Cross-Modal Search and Exploration of Greek Painted Pottery

Optimal Lateral Displacement in Automatic Close-Range Photogrammetry

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