Archaeological fragment characterization and 3D reconstruction based on projective GPU depth maps

Belenguer, Carlos Sánchez; Vidal, Eduardo Vendrell

doi:10.1109/vsmm.2012.6365935

Cited by 20 publications

(11 citation statements)

References 15 publications

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“…The results indicated the efficiency of the proposed technique (250 times faster than exhaustive search) (Belenguer & Vidal, 2012).…”

Section: Performed Studies From 2010 To 2019mentioning

confidence: 81%

“…In the literature, a variety of features were defined. These features are categorized in Figure 4: the most commonly used features are the rotational axis and geometric, profile, and color ones (Belenguer & Vidal, 2012;Karasik & Smilansky, 2011;Rasheed & Nordin, 2015). However, in recent years, more attention has been paid to morphological features, which are more difficult to recognize, being asymmetric structures, but are semantically significant and have specific geometric features useful to drive the assembling process (Di Kalasarinis & Koutsoudis, 2019;Lucena et al, 2016).…”

Section: Data Acquisition and Preprocessingmentioning

confidence: 99%

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Review of computer-based methods for archaeological ceramic sherds reconstruction

Eslami

Angelo

Stefano

et al. 2020

Virtual archaeol. rev.

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Potteries are the most numerous finds found in archaeological excavations; they are often used to get information about the history, economy, and art of a site. Archaeologists rarely find complete vases but, generally, damaged and in fragments, often mixed with other pottery groups. By using the traditional manual method, the analysis and reconstruction of sherds are performed by a skilled operator. Reviewed papers provided evidence that the traditional method is not reproducible, not repeatable, time-consuming and its results have great uncertainties. To overcome the aforementioned limits, in the last years, researchers have made efforts to develop computer-based methods for archaeological ceramic sherds analysis, aimed at their reconstruction. To contribute to this field of study, in this paper, a comprehensive analysis of the most important available publications until the end of 2019 is presented. This study, focused on pottery fragments only, is performed by collecting papers in English by the Scopus database using the following keywords: “computer methods in archaeology", "3D archaeology", "3D reconstruction", "automatic feature recognition and reconstruction", "restoration of pottery shape relics”. The list is completed by additional references found through the reading of selected papers. The 53 selected papers are divided into three periods of time. According to a detailed review of the performed studies, the key elements of each analyzed method are listed based on data acquisition tools, features extracted, classification processes, and matching techniques. Finally, to overcome the actual gaps some recommendations for future researches are proposed.Highlights:<ul><li>The traditional manual method for reassembling sherds is very time-consuming and costly; it also requires a great deal effort from skilled archaeologists in repetitive and routine activities.</li><li>Computer-based methods for archaeological ceramic sherds reconstruction can help archaeologists in the above-mentioned repetitive and routine activities.</li><li>In this paper, the state-of-the-art computer-based methods for archaeological ceramic sherds reconstruction are reviewed, and some recommendations for future researches are proposed.</li></ul>

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“…The results indicated the efficiency of the proposed technique (250 times faster than exhaustive search) (Belenguer & Vidal, 2012).…”

Section: Performed Studies From 2010 To 2019mentioning

confidence: 81%

Section: Data Acquisition and Preprocessingmentioning

confidence: 99%

Review of computer-based methods for archaeological ceramic sherds reconstruction

Eslami

Angelo

Stefano

et al. 2020

Virtual archaeol. rev.

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“…Belenguer et al . [BV12] put particular emphasis on implementation efficiency, speeding up geometric transformations, visibility tests and discretization operations by pre‐calculating data and by moving all heavy calculations to the GPU.…”

Section: Micro‐geometrymentioning

confidence: 99%

A Survey of Geometric Analysis in Cultural Heritage

Pintus

Pal

Yang

et al. 2015

Computer Graphics Forum

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We present a review of recent techniques for performing geometric analysis in cultural heritage applications. The survey is aimed at researchers in the areas of computer graphics, computer vision, and cultural heritage computing, as well as to scholars and practitioners in the cultural heritage field. The problems considered include shape perception enhancement, restoration and preservation support, monitoring over time, object interpretation, and collection analysis. All of these problems typically rely on an understanding of the structure of the shapes in question at both a local and global level. In this survey, we discuss the different problem forms and review the main solution methods, aided by classification criteria based on the geometric scale at which the analysis is performed and the cardinality of the relationships among object parts exploited during the analysis. We finalize the report by discussing open problems and future perspectives.

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“…Significant developments in computer technologies have improved the reconstruction procedures for fragmented archaeological objects [5–9]; a large proportion of this has relied on the fact that pots are axially symmetric. Some researchers have proposed a complete framework with which to automatically assemble pots from 3D fragments [10,11]. These authors have assumed that the objects have been made using a potter’s wheel, and as such they rely upon the axial symmetry around the center of an object in order to reconstruct it from its fragments.…”

Section: Introductionmentioning

confidence: 99%

Reconstruction algorithm for archaeological fragments using slope features

Rasheed

Nordin

2020

ETRI Journal

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The reconstruction of archaeological fragments in 3D geometry is an important problem in pattern recognition and computer vision. Therefore, we implement an algorithm with the help of a 3D model to perform reconstruction from the real datasets using the slope features. This approach avoids the problem of gaps created through the loss of parts of the artifacts. Therefore, the aim of this study is to assemble the object without previous knowledge about the form of the original object. We utilize the edges of the fragments as an important feature in reconstructing the objects and apply multiple procedures to extract the 3D edge points. In order to assign the positions of the unknown parts that are supposed to match, the contour must be divided into four parts. Furthermore, to classify the fragments under reconstruction, we apply a backpropagation neural network. We test the algorithm on several models of ceramic fragments. It achieves highly accurate results in reconstructing the objects into their original forms, in spite of absent pieces.

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Archaeological fragment characterization and 3D reconstruction based on projective GPU depth maps

Cited by 20 publications

References 15 publications

Review of computer-based methods for archaeological ceramic sherds reconstruction

Review of computer-based methods for archaeological ceramic sherds reconstruction

A Survey of Geometric Analysis in Cultural Heritage

Reconstruction algorithm for archaeological fragments using slope features

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