On introducing an image-based 3D reconstruction method in archaeological excavation practice

We have examined image-based 3D modeling for the generation of orthophotos and digital surface models of archaeological surfaces and features. Our results suggest that image-based 3D modeling can be both a time-efficient and cost-effective as well as a scientific valuable method to document archaeological excavations. Although there are limitations, these are greatly surpassed by the possibilities. We believe that image-based 3D modeling can cause a(n) (r)evolution in archaeological excavation practice.

Gradual adaption with memory mechanism for image-based 3D model retrieval

Image-based 3D modeling is an effective method for reconstructing large-scale scenes, especially city-level scenarios. In the image-based modeling pipeline, obtaining a watertight mesh model from a noisy multi-view stereo point cloud is a key step toward ensuring model quality. However, some state-of-the-art methods rely on the global Delaunay-based optimization formed by all the points and cameras; thus, they encounter scaling problems when dealing with large scenes. To circumvent these limitations, this study proposes a scalable point-cloud meshing approach to aid the reconstruction of city-scale scenes with minimal time consumption and memory usage. Firstly, the entire scene is divided along the x and y axes into several overlapping chunks so that each chunk can satisfy the memory limit. Then, the Delaunay-based optimization is performed to extract meshes for each chunk in parallel. Finally, the local meshes are merged together by resolving local inconsistencies in the overlapping areas between the chunks. We test the proposed method on three city-scale scenes with hundreds of millions of points and thousands of images, and demonstrate its scalability, accuracy, and completeness, compared with the state-of-the-art methods.

Abstract. Image-based 3D modelling are rather mature nowadays with well-acquired images through standard photogrammetric processing pipeline, while fusing 3D dataset generated from images with different views for surface reconstruction remains to be a challenge. Meshing algorithms for image-based 3D dataset requires visibility information for surfaces and such information can be difficult to obtain for 3D point clouds generated from images with different views, sources, resolutions and uncertainties. In this paper, we propose a novel multi-source mesh reconstruction and texture mapping pipeline optimized to address such a challenge. Our key contributions are 1) we extended state-of-the-art image-based surface reconstruction method by incorporating geometric information produced by satellite images to create wide-area surface model. 2) We extended a texture mapping method to accommodate images acquired from different sensors, i.e. side-view perspective images and satellite images. Experiments show that our method creates conforming surface model from these two sources, as well as consistent and well-balanced textures from images with drastically different radiometry (satellite images vs. street-view level images). We compared our proposed pipeline with a typical fusion pipeline - Poisson reconstruction and the results show that our pipeline shows distinctive advantages.

During the last twenty years archaeology has experienced a technological revolution that spans scientific achievements and day-to-day practices. The tools and methods from this digital change have also strongly impacted archaeology. Image-based 3D modeling is becoming more common when documenting archaeological features but is still not implemented as standard in field excavation projects. When it comes to integrating zooarchaeological perspectives in the interpretational process in the field, this type of documentation is a powerful tool, especially regarding visualization related to reconstruction and resolution. Also, with the implementation of image-based 3D modeling, the use of digital documentation in the field has been proven to be time- and cost effective (e.g., De Reu et al. 2014; De Reu et al. 2013; Dellepiane et al. 2013; Verhoeven et al. 2012). Few studies have been published on the digital documentation of faunal remains in archaeological contexts. As a case study, the excavation of the infill of a clay bin from building 102 in the Neolithic settlement of Ҫatalhöyük is presented. Alongside traditional documentation, infill was photographed in sequence at each second centimeter of soil removal. The photographs were processed with Agisoft Photoscan. Seven models were made, enabling reconstruction of the excavation of this context. This technique can be a powerful documentation tool, including recording notes of zooarchaeological significance, such as markers of taphonomic processes. An important methodological advantage in this regard is the potential to measure bones in situ in for analysis after excavation.

For more than a decade, Terrestrial Laser Scanning (TLS) has been a primary remote sensing technique for disciplines related to archaeology, architecture, built heritage, earth science, metrology, and land survey. The increasing precision, range, and survey speed of TLS make this technology even more viable for large-scale data capturing in the Age of Sensing. This chapter reviews the state of the art of Terrestrial Laser Scanning in 2015 with the aim to assess its applications in a context of lower data capturing costs for alternative technologies, such as new commodity sensors, Image-based 3D Modeling, Unmanned Aerial Systems (UAS), optical 3D scanning, and Airborne Laser Scanning. More specifically, TLS still maintains a fundamental role in the documentation and interpretation of archaeological contexts at intrasite scale: (i) Terrestrial Laser Scanning delivers high-fidelity data of surfaces and structures of buildings as well as ultra-precise measurements of the morphology of stratigraphic layers; (ii) research in remote sensing proved that TLS point clouds can be successfully interpolated with data recorded with other instruments and techniques, such as magnetometry, Ground Penetrating Radar, Unmanned Aerial Vehicles, Image-Based Modeling, in order to generate hybrid documentation and new knowledge on natural and cultural heritage sites. Inevitably, the current advancements in TLS bring new questions. For example, how can micro-differences only visible in the point clouds change the analysis and interpretation of layers and buildings? How to improve the monitoring and conservation of a site via automated analysis of TLS data? How to enhance the mapping process of built-heritage using data segmentation or semi-automatic feature extraction of TLS point clouds? This chapter proposes a new approach to TLS based on multi-modal capture workflows, semi-automated post processing, online archiving, and online visualization and management of point clouds with the aim to open new horizons for digital archaeology, architectural survey, and heritage conservation .

Minimally invasive treatment of solid cancers, especially in the breast and liver, remains clinically challenging, despite a variety of treatment modalities, including radiofrequency ablation (RFA), microwave ablation or high-intensity focused ultrasound. Each treatment modality has advantages and disadvantages, but all are limited by placement of a probe or US beam in the target tissue for tumor ablation and monitoring. The placement is difficult when the tumor is surrounded by large blood vessels or organs. Patient-specific image-based 3D modeling for thermal ablation simulation was developed to optimize treatment protocols that improve treatment efficacy. A tissue-mimicking breast gel phantom was used to develop an image-based 3D computer-aided design (CAD) model for the evaluation of a planned RF ablation. First, the tissue-mimicking gel was cast in a breast mold to create a 3D breast phantom, which contained a simulated solid tumor. Second, the phantom was imaged in a medical MRI scanner using a standard breast imaging MR sequence. Third, the MR images were converted into a 3D CAD model using commercial software (ScanIP, Simpleware), which was input into another commercial package (COMSOL Multiphysics) for RFA simulation and treatment planning using a finite element method (FEM). For validation of the model, the breast phantom was experimentally ablated using a commercial (RITA) RFA electrode and a bipolar needle with an electrosurgical generator (DRE ASG-300). The RFA results obtained by pre-treatment simulation were compared with actual experimental ablation. A 3D CAD model, created from MR images of the complex breast phantom, was successfully integrated with an RFA electrode to perform FEM ablation simulation. The ablation volumes achieved both in the FEM simulation and the experimental test were equivalent, indicating that patient-specific models can be implemented for pre-treatment planning of solid tumor ablation. A tissue-mimicking breast gel phantom and its MR images were used to perform FEM 3D modeling and validation by experimental thermal ablation of the tumor. Similar patient-specific models can be created from preoperative images and used to perform finite element analysis to plan radiofrequency ablation. Clinically, the method can be implemented for pre-treatment planning to predict the effect of an individual's tissue environment on the ablation process, and this may improve the therapeutic efficacy.

High precision analysis of an embryonic extensional fault-related fold using 3D orthorectified virtual outcrops: The viewpoint importance in structural geology

BIM-based task-level planning for robotic brick assembly through image-based 3D modeling

We address the problem of automatically fusing hyperspectral data of a digitized scene with an image-based 3D model, overlapping the same scene, in order to associate material spectra with corresponding height information for improved scene understanding. The datasets have been independently collected at different spatial resolutions by different aerial platforms and the georegistration information about the datasets is assumed to be insufficient or unavailable. We propose a method to solve the fusion problem by associating Scale Invariant Feature Transform (SIFT) descriptors from the hyperspectral data with the corresponding 3D point cloud in a large scale 3D model. We find the correspondences efficiently without affecting matching performance by limiting the initial search space to the centroids obtained after performing k-means clustering. Finally, we apply the Optimal Randomized RANdom Sample Consensus (RANSAC) algorithm to enforce geometric alignment of the hyperspectral images onto the 3D model. We present preliminary results that show the effectiveness of the method using two large datasets collected from drone-based sensors in an urban setting.

The prior knowledge is the significant supplement to image-based 3D modeling algorithms for refining the fragile consistency-based stereo. In this paper, we review the image-based 3D modeling problem according to prior categories, i.e., classical priors and specific priors. The classical priors including smoothness, silhouette and illumination are well studied for improving the accuracy and robustness of the 3D reconstruction. In recent years, various specific priors which take advantage of Manhattan rule, geometry template and trained category features have been proposed to enhance the modeling performance. The advantages and limitations of both kinds of priors are discussed and evaluated in the paper. Finally, we discuss the trend and challenges of the prior studies in the future.

This paper presents a general texture mapping framework for image-based 3D modeling. It aims to generating seamless texture map for 3D model created by real-world photos under uncontrolled environment. Our proposed method addresses two challenging problems: 1) texture discontinuity due to system error in 3D modeling from self-calibration; 2) color/lighting difference among images due to real-world uncontrolled environments. The general framework contains two stages to resolve these problems. The first stage globally optimizes the registration of texture patches and triangle faces with Markov Random Field (MRF) to optimize texture mosaic. The second stage does local radiometric correction to adjust color difference between texture patches and then blend texture boundaries to improve color continuity. The proposed method is evaluated on several 3D models by image-based 3D modeling, and demonstrates promising results.

Abstract. This paper presents a "standard" method that is being developed by ARESlab of Rome's La Sapienza University for the documentation and the representation of the archaeological artifacts and structures through automatic photogrammetry software. The image-based 3D modeling technique was applied in two projects: in Sarno and in Rome. The first is a small city in Campania region along Via Popilia, known as the ancient way from Capua to Rhegion. The interest in this city is based on the recovery of over 2100 tombs from local necropolis that contained more than 100.000 artifacts collected in "Museo Nazionale Archeologico della Valle del Sarno". In Rome the project regards the archaeological area of Insula Volusiana placed in Forum Boarium close to Sant'Omobono sacred area. During the studies photographs were taken by Canon EOS 5D Mark II and Canon EOS 600D cameras. 3D model and meshes were created in Photoscan software. The TOF-CW Z+F IMAGER® 5006h laser scanner is used to dense data collection of archaeological area of Rome and to make a metric comparison between range-based and image-based techniques. In these projects the IBM as a low-cost technique proved to be a high accuracy improvement if planned correctly and it shown also how it helps to obtain a relief of complex strata and architectures compared to traditional manual documentation methods (e.g. two-dimensional drawings). The multidimensional recording can be used for future studies of the archaeological heritage, especially for the "destructive" character of an excavation. The presented methodology is suitable for the 3D registration and the accuracy of the methodology improved also the scientific value.

This paper introduces web-based 3D media information system. We first address two promising 3D modeling techniques, i.e., image-based 3D modeling and laser scanning based 3D modeling. Especially, we present two approaches of the image-based 3D modeling. One is an off-line approach using multiview images which is captured with single camera and a robot arm. The another one is an on-line approach that extends a commercial triclops camera system. We also utilize a 3D modeling scheme based on a laser scanner and a 3D reverse modeler. Using our 3D modeling environments, we construct several kinds of 3D models. We also implement web-based 3D media information management and retrieval system using XML data server, which provides services of 3D models. Our web-based 3D media information system has a goal of services of various types of 3D models and contents through WWW, which is currently focused on the development and management of 3D models of Korea cultural heritage.

Augmented reality (AR), in conjunction with 3D geovisualization methods, can provide significant support in monitoring geoconservation activities in protected geosites, such as the excavation process in fossil sites. The excavation process requires a monitoring methodology that will provide a complete and accurate overview of the fossils, their dimensions, and location within the different pyroclastic horizons, and the progress of the excavation works. The main purpose of this paper is the development of a user-friendly augmented map application, specifically designed for tracking the position of petrified tree trunks, providing information for their geometric features, and mapping the spatiotemporal changes occurring in the surrounding space. It also aims to probe whether the rapid acquisition of a 4K video can generate cartographic derivatives of petrified findings during a geosite excavation. A database accumulated 2D and 3D cartographic information, while the geovisualization environment displayed the surface alterations, at two scales: a) 1:500 (excavation area) and b) 1:50 (trench level). Unmanned aerial systems (UASs), used for data acquisition in three excavation periods, consisted of two flights at two different altitudes: one to record changes throughout the study area and the other to provide information on trunks at trench level, via a high-resolution (4K) video. Image-based 3D modeling followed, in which image georeferencing was conducted with ground control points (GCPs). Finally, 2D and 3D geovisualizations were created to depict the excavation changes through time. The cartographic products generated at two cartographic scales depicted the spatiotemporal changes of the excavation.