Search Results (5)

The modeling of real objects digitally is an area that has generated a high demand due to the need to obtain systems that are able to reproduce 3D objects from real objects. To this end, several techniques have been proposed to model objects in a computer, with the fringe profilometry technique being the one that has been most researched. However, this technique has the disadvantage of generating Moire noise that ends up affecting the accuracy of the final 3D reconstructed object. In order to try to obtain 3D objects as close as possible to the original object, different techniques have been developed to attenuate the quasi/periodic noise, namely the application of convolutional neural networks (CNNs), a method that has been recently applied for restoration and reduction and/or elimination of noise in images applied as a pre-processing in the generation of 3D objects. For this purpose, this work is carried out to attenuate the quasi/periodic noise in images acquired by the fringe profilometry technique, using a modified CNN-Multiresolution network. The results obtained are compared with the original CNN-Multiresolution network, the UNet network, and the FCN32s network and a quantitative comparison is made using the Image Mean Square Error E (IMMS), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Profile (MSE) metrics. Full article

In this paper, we introduce applications of Artificial Intelligence techniques, such as Decision Trees and Semantic Reasoning, for semi-automatic and semantic-model-based decision-making for archaeological feature comparisons. This paper uses the example of Roman African Red Slip Ware (ARS) and the collection of ARS at the LEIZA archaeological research institute. The main challenge is to create a Digital Twin of the ARS objects and artefacts using geometric capturing and semantic modelling of archaeological information. Moreover, the individualisation and comparison of features (appliqués), along with their visualisation, extraction, and rectification, results in a strategy and application for comparison of these features using both geometrical and archaeological aspects with a comprehensible rule set. This method of a semi-automatic semantic model-based comparison workflow for archaeological features on Roman ceramics is showcased, discussed, and concluded in three use cases: woman and boy, human–horse hybrid, and bears with local twists and shifts. Full article

The work described in the paper emphasizes the importance of integrating imagery and laser scanner techniques (TLS) to optimize the geometry and visual quality of Heritage BIM. The fusion-based workflow was approached during the recording of Zee Ain Historical Village in Saudi Arabia. The village is a unique example of traditional human settlements, and represents a complex natural and cultural heritage site. The proposed workflow divides data integration into two levels. At the basic level, UAV photogrammetry with enhanced mobility and visibility is used to map the ragged terrain and supplement TLS point data in upper and unaccusable building zones where shadow data originated. The merging of point clouds ensures that the building’s overall geometry is correctly rebuilt and that data interpretation is improved during HBIM digitization. In addition to the correct geometry, texture mapping is particularly important in the area of cultural heritage. Constructing a realistic texture remains a challenge in HBIM; because the standard texture and materials provided in BIM libraries do not allow for reliable representation of heritage structures, mapping and sharing information are not always truthful. Thereby, at the second level, the workflow proposed true orthophoto texturing method for HBIM models by combining close-range imagery and laser data. True orthophotos have uniform scale that depicts all objects in their respective planimetric positions, providing reliable and realistic mapping. The process begins with the development of a Digital Surface Model (DSM) by sampling TLS 3D points in a regular grid, with each cell uniquely associated with a model point. Then each DSM cell is projected in the corresponding perspective imagery in order to map the relevant spectral information. The methods allow for flexible data fusion and image capture using either a TLS-installed camera or a separate camera at the optimal time and viewpoint for radiometric data. The developed workflows demonstrated adequate results in terms of complete and realistic textured HBIM, allowing for a better understanding of the complex heritage structures. Full article

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 (σ_z = 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. Full article

For decades, researchers have been trying to create intuitive virtual environments by blending reality and virtual reality, thus enabling general users to interact with the digital domain as easily as with the real world. The result is “augmented reality” (AR). AR seamlessly superimposes virtual objects on to a real environment in three dimensions (3D) and in real time. One of the most important parts that helps close the gap between virtuality and reality is the marker used in the AR system. While pictorial marker and bar-code marker are the two most commonly used marker types in the market, they have some disadvantages in visual and processing performance. In this paper, we present a novelty method that combines the bar-code with the original feature of a colour picture (e.g., photos, trading cards, advertisement’s figure). Our method decorates on top of the original pictorial images additional features with a single stereogram image that optically conceals a multi-level (3D) bar-code. Thus, it has a larger capability of storing data compared to the general 1D barcode. This new type of marker has the potential of addressing the issues that the current types of marker are facing. It not only keeps the original information of the picture but also contains encoded numeric information. In our limited evaluation, this pictorial bar-code shows a relatively robust performance under various conditions and scaling; thus, it provides a promising AR approach to be used in many applications such as trading card games, educations, and advertisements. Full article