Search

The article presents a practical method that combines low-cost camera systems with remotely operated vehicles (ROVs) to accomplish a comprehensive but economically feasible underwater survey of large hydropower infrastructures. Typically, inspecting reservoirs entails draining them off to allow for visual inspections, which are time-intensive, pose risks to operators' safety and are associated with generation losses. In this regard, ROVs are a much safer and more efficient alternative to traditional methods. The study was conducted at the Pack reservoir in Austria, where a reference framework was set up using terrestrial laser scanning and checkerboard markings for the above-water components. A ROV equipped with a GoPro camera and lighting system for the underwater recordings has been employed. Via a close-range photogrammetric approach, it was possible to generate 3D point clouds of the submerged infrastructure with a survey-grade accuracy level. Various strategies were explored to perform bundle block adjustment (BBA), among these were strategies where ground control points (GCPs) were used, strategies without the use of GCPs but pre-calibrated initial camera parameters and strategies with a combination of using both GCPs and pre-calibrated camera parameters in the BBA. The deployment of an inspection technique using low-cost sensors that can generate highly detailed three-dimensional models of submerged infrastructure areas is presented and discussed, allowing easy detection and localization for maintenance inspection, all while being cost-effective. The paper strengthens the suggestion of best practices that optimize camera settings, considering the effect of electronic image stabilization, suggesting its avoidance, and using advanced calibration methods.

Photogrammetry is a valuable tool for 3D documentation, mapping, and monitoring of underwater environments. However, the ground control surveys necessary for georeferencing and validation of the reconstructed bathymetry are difficult and time consuming to perform underwater, and thus impractical to scale to larger areas. Underwater direct georeferencing, using a differential GNSS receiver synchronized with an underwater camera system, offers an attractive alternative to surveying underwater ground control points in conditions when the seafloor is clearly visible from the surface. In this paper, the design of an underwater direct georeferencing system using mostly commercial off the shelf components is presented. The accuracy of the system is evaluated against geodetic survey based on trilateration and leveling, as well as by RTK (real time kinematic) positioning using a tilt-compensated GNSS receiver mounted on an extended pole to allow measurements of points in up to 7 m in water depth. Tests were conducted in a controlled outdoor pool setting with depths from 1–3 m, as well as in a 10 m × 10 m test plot established on the seafloor in a near-shore environment by Catalina Island, California at depths from 4–10 m. Comparing the geometry of the photogrammetric reconstruction with the geodetic survey yielded sub centimeter consistency, and 1 mm accuracy in length measurement was achieved when compared with calibrated 0.5 m scale bars. Through repeated surveys of the same area, repeatability of georeferencing is demonstrated within expectations for differential GNSS positioning, with horizontal errors at sub centimeter level, and vertical errors of up to 3 cm in the worst cases. These tests demonstrate the benefits of the underwater direct georeferencing approach in shallow waters, which can be scaled up much more easily than measuring underwater ground control points with traditional approaches, making this an ideal option for collecting accurate bathymetry of the seafloor over large coastal areas with clear waters.

Three-dimensional reference points (RPs) are fundamental for datum definition and metric validation in many photogrammetric applications, often used as ground control points (GCPs) to constrain the bundle adjustment solution. Nevertheless, survey operations underwater present challenges due to the physical characteristics of the water itself and the technological limitations of available instruments. Traditional methods to collect RPs underwater rely on direct geodetic measurements like slope distances, height differences, and depths from a dive computer. These methods can be time-consuming and impractical to scale up to large areas, particularly in deeper waters. This paper reports on the use of a custom-developed low-cost pressure sensor to measure depths and height differences of underwater RPs with survey-grade accuracy. Laboratory and open water tests demonstrated the method's potential, achieving an RMSEZ of less than 1 mm over a 1.5 m height range in the laboratory in static water and a sub-centimetre RMSE of relative depth differences in shallow water tests carried out in two different locations at sea with maximum significant wave height of 9 cm. The sensor proved its effectiveness also for constraining a corridor-like underwater photogrammetric survey reducing the bending of the 3D model with respect to the free network solution (RMSEZ lowered from 10 cm to less than 1 cm). The preliminary tests with the presented approach proved several advantages against other consolidated methods, including cost reduction (compared to commercial survey instruments), rapidity, safety, and accuracy, especially at depths greater than 3–5 m where other approaches (e.g., GNSS or topographic measures) cannot be applied.

Underwater photogrammetry presents unique challenges due to the optical properties of water that, if not correctly taken into account, might affect the quality of the survey and the related 2D and 3D products. It is recognized nowadays the importance to train newcomers to underwater surveying, and extend and consolidate the knowledge of best practices for underwater data acquisition. Starting from this consideration, we propose the development of POSER, a 3D simulation framework designed to facilitate the teaching of underwater imaging principles. The project, an ISPRS Educational and Capacity Building Initiative, is built upon the open-source platform Blender, incorporating realistic modelling of the physical properties of water, including light refraction, scattering, and absorption phenomena, to simulate underwater surveying conditions. We foster a learning-by-doing approach, providing users with ready-to-use application scenarios inspired by real-life case studies. They will cover a range of application fields, from marine ecology to archaeology and subsea metrology, and allow users to address the complexities of underwater surveying practices. This paper introduces POSER to the community, presenting its educational vocation and describing its constituent components.

Benchmark datasets have become increasingly widespread in the scientific community as a method of comparison, validation, and improvement of theories and techniques thanks to more affordable means for sharing. While this especially holds for test sites and data collected above the water, publicly accessible benchmark activities for geospatial analyses in the underwater environment are not very common. Applying geomatic techniques underwater is challenging and expensive, especially when dealing with deep water and offshore operations. Moreover, benchmarking requires ground truth data for which, in water, several open issues exist concerning geometry and radiometry. Recognizing this scientific and technological challenge, the NAUTILUS (uNder And throUgh waTer datasets for geospatIaL stUdieS) project aims to create guidelines for new multi-sensor/cross-modality benchmark datasets. The project focuses on (i) surveying the actual needs and gaps in through and under-the-water geospatial applications through a questionnaire and interviews, (ii) launching a unique publicly available database collecting already existing datasets scattered across the web and literature, (iii) designing and identifying proper test site(s) and methodologies to deliver to the extended underwater community a brand-new multi-sensor/cross-modality benchmark dataset. The project outputs are available to researchers and practitioners in underwater measurements-related domains, as they can now access a comprehensive tool providing a synthesis of open questions and data already available. In doing so, past research efforts to collect and publish datasets have received additional credit and visibility.

Underwater photogrammetry is often hampered by chromatic aberration, leading to degraded 2D and 3D products. This study investigates the effectiveness of various color enhancement methods in addressing these challenges.Theoretical considerations indicate that light penetration depth varies inversely with wavelength, causing underwater images to exhibit a blue or green cast with increasing depth. Color enhancement techniques can restore natural colors by compensating for this spectral attenuation. Additionally, scattering, caused by light reflected by particles in the water, can introduce haze into underwater images. Color enhancement can mitigate scatter and improve image clarity. In this contribution, to quantitatively evaluate color enhancement methods, we compare original images with images processed using gray-world assumption methods and physical methods that account for the physical properties of light underwater. Using artificial intelligence (AI) for underwater image color enhancement, a data-driven approach was also employed. These methods were applied to a case study concerning a Roman Navis Lapidaria shipwreck carrying five monumental cipollino marble columns at a depth of 4.5 meters in the Porto Cesareo Marine Protected Area (Italy). These methods were compared quantitatively and qualitatively, and the results are presented and discussed.

In the framework of mapping underwater environments, Posidonia Oceanica (PO) is a fundamental indicator for environmental monitoring and related studies and analyses for climate change. The POSEIDON project aims to study, develop and test new methodologies to provide knowledge, as well as ultra-high-resolution (UHR) and beyond ultra-high-resolution (BUHR) mapping and monitoring data for the conservation of the PO and related meadows and banquettes in the Mediterranean area. The project is funded by the National Recovery and Resilience Plan and stems from the recommendation of international organizations (European Environmental Directives, Mediterranean PO Network, International Partnership for Blue Carbon, Intergovernmental Oceanographic Commission of UNESCO in the Save the Wave project). Starting from new integrated survey methods and legacy data, the PO, ichthyofauna and seagrass banquettes will be mapped to understand their evolution and extract indicators and useful trends. Furthermore, the produced information will be stored and shared in a webGIS and a dedicated app to prevent unexpected damages during sailing or other activities. POSEIDON will use imaging sensors (RGB and multi/hyperspectral cameras) to extract information. With specific lighting equipment for significant water depths, these sensors will be conducted (by scuba divers or Autonomous Underwater Vehicles) next to the object to acquire BUHR data. Finally, to monitor the fauna (fish, other species, invertebrates), terrestrial and underwater videogrammetry will be applied using mono and stereo-cameras with object detection algorithms.

The first edition of the SUNRISE (Seashore and UNderwater documentation of aRchaeological herItage palimpSests and Environment) summer school was carried out in Marina di Ragusa in Sicily (Italy) from 3rd to 9th September 2022. It was jointly organized by Politecnico di Torino, IUAV, University of Sassari, FBK, University of Udine and the University of Modena and Reggio Emilia with the support of SIFET, ISPRS Student Consortium, private companies (Images, Microgeo, Stonex, Leica and Geomax) and the municipality of Santa Croce Camerina.The five days of summer school were attended by 20 students from Europe, Asia and USA. After the first day of lectures focused on the theoretical basis of surveying, photogrammetry, LiDAR, and SLAM, the field activities took place in a submerged and terrestrial scenario. The underwater surveying involved a submerged amphora, and the terrestrial activity was focused on the Arab bath of Mezzagnone, a 6th-century AD building that has been fully preserved until today. The paper deal with this experience and underline the followed approach. Finally some results achieved by the students are reported.

Browsing the scientific and professional literature it appears that the concept of mobile mapping underwater is not as common as in ‘terrestrial’ applications. Nevertheless, exploring and mapping the ocean’s depths is a priority challenge for humankind, today more than ever. Radio waves, such as the GNSS or UWB signal, have a very limited transmission underwater, resulting in the absence of an underwater global positioning system. Consequently, the main sounding methods (i.e., depth measuring systems) are based on the fusion of inertial and acoustic sensors, which allow for systematic mapping of vast seafloor areas. However, photogrammetric surveying methods are preferred when high resolution and reliable colour information are essential aspects in the project economy. This class of approaches include visual odometry and visual SLAM (vSLAM), which represent a valid tool for navigation and positioning in GNSS-denied environments, such as underwater. In this paper, we present a portable underwater mobile mapping system, named FROG, which implements a vSLAM based solution to guide the survey according to photogrammetric principles. FROG is built upon the Guided Photogrammetry - GuPho concept and, thanks to its modular design, can be used by a diver or installed on a micro ROV and controlled remotely from a support vessel. In the paper, FROG characteristics will be detailed, and its potentialities demonstrated in real case applications at sea and in lakes.

The bond with computer vision and robotics is revolutionizing the traditional surveying approaches. Algorithms such as visual odometry and SLAM are embedded in surveying systems to make on-site and processing operations more efficient both in terms of time and quality of the achieved results. In this paper, we present the latest developments on GuPho, a mobile mapping concept based on photogrammetry that leverages a vSLAM solution to provide innovative and unique features supporting the image acquisition and optimising the processing steps. These include visual feedback on ground sample distance and maximum allowed speed to avoid motion blur. Two efficient image acquisition strategies, based on geometric principles, are implemented to optimise the disk storage, avoiding unnecessary redundancy. Moreover, an innovative automatic exposure control that adjusts the shutter speed or gain based on the tracked object in 3D is part of the system. The paper reports the motivations behind the design choices, details the hardware and software components, discusses several case studies to showcase the potentialities of our low-cost, lightweight, and portable modular prototype system.

Refraction effects, their description and modeling are important aspects of underwater and multimedia photogrammetry. For hemispherical interfaces, the usual approach to refraction is to rely on standard pinhole representations, e.g. by employing the Brown model. This is strictly only possible if entrance pupil of the lens and dome center coincide which is not trivial to achieve. However, simulations and other authors show that systematic residual errors occur with these approaches up to considerable margins if offsets of some millimeters are present. Hence, we propose a novel efficient, yet strict optimization algorithm to account for offsets between dome port centers and entrance pupil. It is about two orders of magnitude faster than standard ray tracing implementations that account for refraction while providing similar or equal results. The algorithm is employed for analysis on a simulation and two real data sets and performance of additionally estimating the dome center is investigated. Our method is capable of improving accuracy in one data set at a maximum of 30% but even so cannot provide improvements for the second data sets. An explicit calibration model is hence to be chosen carefully and most likely relies on the offset’s margins and each individual application.

Long-term monitoring projects are becoming more than ever crucial in assessing the effects of climate change on marine communities, especially in Antarctica, where these changes are expected to be particularly dramatic. Detailed studies of the Antarctic benthos are in fact particularly important for a better understanding of benthos dynamics and potential climate-driven shifts. Here, due to the extreme fragility of benthic communities, non-destructive techniques represent the best solution in long-term monitoring programs. In this paper we report new results from 2017, 2018, 2019 photogrammetric campaigns within the Italian National Antarctic Research Program (PNRA). A new protocol of data acquisition and multi-temporal processing that provides co-registered 3D point clouds between the three years without control points nor direct georeferencing methods is presented. This is achieved by adding a level of image understanding leveraging semantic segmentation with convolutional neural network (CNN) of the benthic features. Slow growing (estimated less than a mm per year) organisms, such as Corallinales (Rhodophyta algae), represent a natural stable pattern, leveraged to automatically orient in the same reference system the photogrammetric surveys of different epochs. This approach is also proved to be effective in improving the orientation of adjacent strips acquired within the same campaign. Within the paper an in depth analysis of the achieved results shows the effectiveness of the implemented procedure.

Image stabilisation (IS) is a family of approaches whose aim is to reduce motion blur in still images and shaking effect in video frames. A variety of techniques are currently implemented in cameras and camcorders: some involve hardware solutions, other are software approaches. In general, IS for still photography entails hardware in-camera or in-lens solutions. Video stabilisation, on the other hand, can be accomplished with software algorithms, either in real-time within the camera or in post-processing.Whereas IS aids photography and video making, its influence on the photogrammetric 3D modelling process has not been investigated. This article addresses this aspect. To this purpose, several laboratory and real-world tests were carried out, whose results showed that IS must be disabled when accuracy matters in photogrammetric projects. Details are provided in the manuscript.

Cultural Heritage (CH) resources are partial, heterogeneous, discontinuous, and subject to ongoing updates and revisions. The use of semantic web technologies associated with 3D graphical tools is proposed to improve access, exploration, exploitation and enrichment of these CH data in a standardized and more structured form. This article presents the monitoring work developed for more than ten years on the excavation of the Xlendi site. Around an exceptional shipwreck, the oldest from the Archaic period in the Western Mediterranean, we have set up a unique excavation at a depth of 110m assisted by a rigorous and continuous photogrammetry campaign. All the collected results are modelled by an ontology and visualized with virtual and augmented reality tools that allow a bidirectional link between the proposed graphical representations and the non-graphical archaeological data. It is also important to highlight the development of an innovative 3D mobile app that lets users study and understand the site as well as experience sensations close to those of a diver visiting the site.

Photogrammetry needs known geometric elements to provide metric traceable measurements. These known elements can be a distance between two three-dimensional object points or two camera stations, or a combination of known coordinates and/or angles to solve the seven degrees of freedom that lead to rank deficiency of the normal-equation matrix. In this paper we present a novel approach for scaling and levelling to the local vertical direction an underwater photogrammetric survey. The developed methodology is based on a portable low-cost device designed and realized by the authors that uses depth measurements from a high resolution pressure sensor. The prototype consists of a data logger featuring a pressure sensor synchronized with a digital camera in its underwater pressure housing. The modular design, with optical communication and synchronization, provides great flexibility not requiring the camera housing to undergo any hardware modifications. The proposed methodology allows for a full 3D levelling transformation comprising two angles, a vertical translation and a scale factor and can work for surveying scenes extending horizontally, vertically or both. The paper presents the theoretical principles, an overview of the developed system together with preliminary calibration results. Tests in a lake and at sea are reported. An accuracy better than 1:5000 on the length measurement was achieved in calm water conditions.

During underwater investigations, whatever the mission objective and the type of vehicle, obstacles detection and avoidance are essential tasks. They can either represent a target of interest that is the object of the mission or, on the contrary, represent obstacles that can hinder or affect the navigation of the vehicle. The underwater optical cameras that are usually fitted to underwater vehicles only offer a narrow field of view. The absorption of electromagnetic waves in the first few meters and the diffusion of light by the particles limit the use of these sensors to only a few meters range. The use of acoustic sensors, such as the forward looking sonar (FLS), is then necessary to enlarge the volume in which a target can be detected during the progression of the vehicle. Traditionally, sonars featured mechanical rotating parts, but lately bidirectional forward looking sonar, which directly produces a 2D image of the area, are becoming more and more common. Although these sonars can operate at frequency higher than 1MHz, their spatial resolution remains much lower if compared to current optical sensors and can be insufficient to identify and characterize a target. The combination of these two sensors in an operational scenario is essential to take advantage of each technology. In this paper we describe a low cost, multi-sensor, underwater survey solution for the identification, tracking, and 3D mapping of targets. After a description of the architecture of the opto-acoustics data acquisition and processing platform, we will focus on the calibration of the rigid transformation between the two sensors.

Uncontrolled refraction of optical rays in underwater photogrammetry is known to reduce its accuracy potential. Several strategies have been proposed aiming at restoring the accuracy to levels comparable with photogrammetry applied in air. These methods are mainly based on rigours modelling of the refraction phenomenon or empirical iterative refraction corrections. The authors of this contribution have proposed two mitigation strategies of image residuals systematic patterns in the image plane: (i) empirical weighting of image observations as function of their radial position; (ii) iterative look-up table corrections computed in a squared grid. Here, a novel approach is developed. It explicitly takes into account the object point-to-camera distance dependent error introduced by refraction in multimedia photogrammetry. A polynomial correction function is iteratively computed to correct the image residuals clustered in radial slices in the image plane as function of the point-to-camera distance. The effectiveness of the proposed method is demonstrated by simulations that allow to: (i) separate the geometric error under investigation from other effects not easily modellable and (ii) have reliable reference data against which to assess the accuracy of the result.

Although fully autonomous mapping methods are becoming more and more common and reliable, still the human operator is regularly employed in many 3D surveying missions. In a number of underwater applications, divers or pilots of remotely operated vehicles (ROVs) are still considered irreplaceable, and tools for real-time visualization of the mapped scene are essential to support and maximize the navigation and surveying efforts. For underwater exploration, image mosaicing has proved to be a valid and effective approach to visualize large mapped areas, often employed in conjunction with autonomous underwater vehicles (AUVs) and ROVs. In this work, we propose the use of a modified image mosaicing algorithm that coupled with image-based real-time navigation and mapping algorithms provides two visual navigation aids. The first is a classic image mosaic, where the recorded and processed images are incrementally added, named 2D sequential image mosaicing (2DSIM). The second one geometrically transform the images so that they are projected as planar point clouds in the 3D space providing an incremental point cloud mosaicing, named 3D sequential image plane projection (3DSIP). In the paper, the implemented procedure is detailed, and experiments in different underwater scenarios presented and discussed. Technical considerations about computational efforts, frame rate capabilities and scalability to different and more compact architectures (i.e. embedded systems) is also provided.

In the last years, vision-based systems have flourished at an unprecedented pace, fuelled by developments in hardware components (higher resolution and higher sensitivity imaging sensors, smaller and smarter micro controllers, just to name a few), as well as in software or processing techniques, with AI (Artificial Intelligence) leading to a landmark revolution. Several disciplines have fostered and benefited from these advances, but, unfortunately, not always in a coordinated and cooperative way.When it comes to image-based sensing techniques, photogrammetry, computer vision and robotic vision have many contact points and overlapping areas. Yet, as for people of different cultures and languages, communicating among the three different communities can be very harsh and disorienting - especially for beginners and non-specialists.Driven by a strong educational and inclusive ambition, the LightCam project is funded by the ISPRS Education and Capacity Building Initiatives 2020 (ECB). The project’s ambition is to act as an interpreter and ease the dialog among the three actors, i.e. photogrammetry, computer vision and robotics. Two intermediation tools will be developed to serve this aim: (i) a dictionary of concepts, terminology and algorithms, in the form of a knowledge base website, and (ii) a code repository, where pieces of code for the conversion between different formulations implemented in available software solutions will be shared.

Systematic errors may result from the adoption of an incomplete functional model that is not able to properly incorporate all the effects involved in the image formation process. These errors very likely appear as systematic residual patterns in image observations and produce deformations of the photogrammetric model in object space. The Brown/Beyer model of self-calibration is often adopted in underwater photogrammetry, although it does not take into account the refraction introduced by the passage of the optical ray through different media, i.e. air and water. This reduces the potential accuracy of photogrammetry underwater. In this work, we investigate through simulations the depth-dependent systematic errors introduced by unmodelled refraction effects when both flat and dome ports are used. The importance of camera geometry to reduce the deformation in the object space is analyzed and mitigation measures to reduce the systematic patterns in image observations are investigated. It is shown how, for flat ports, the use of a stochastic approach, consisting in radial weighting of image observations, improves the accuracy in object space up to 50%. Iterative look-up table corrections are instead adopted to reduce the evident systematic residual patterns in the case of dome ports.

Image-based 3D models generation typically involves three stages, namely: 2D image acquisition, data processing, and 3D surface generation and editing. The availability of different easy-to-use and low-cost image acquisition solutions, combined with open-source or commercial processing tools, has democratized the 3D reconstruction and digital twin generation. But high geometric and texture fidelity on small- to medium-scale objects as well as integrated commercial system for mass 3D digitization are not available. The paper presents our effort to build such a system, i.e. a market-ready multi-camera solution and a customized reconstruction process for mass 3D digitization of small to medium objects. The system is realized as a joint work between industrial and academic partners, in order to employ the latest technologies for the needs of the market. The proposed versatile image acquisition and processing system pushes to the limits the 3D digitization pipeline combining a rigid capturing system with photogrammetric reconstruction methods.

Underwater caves represent the most challenging scenario for exploration, mapping and 3D modelling. In such complex environment, unsuitable to humans, highly specialized skills and expensive equipment are normally required. Technological progress and scientific innovation attempt, nowadays, to develop safer and more automatic approaches for the virtualization of these complex and not easily accessible environments, which constitute a unique natural, biological and cultural heritage. This paper presents a pilot study realised for the virtualization of 'Grotta Giusti' (Fig. 1), an underground semi-submerged cave system in central Italy. After an introduction on the virtualization process in the cultural heritage domain and a review of techniques and experiences for the virtualization of underground and submerged environments, the paper will focus on the employed virtualization techniques. In particular, the developed approach to simultaneously survey the semi-submersed areas of the cave relying on a stereo camera system and the virtualization of the virtual cave will be discussed.

Metrology is fundamental in all the applications that require to qualify, verify and validate measured data according to standards or, in other words, to assess their compliance with predefined tolerances. At sea, metrology is commonly associated with the process of measuring underwater structures, mainly pipeline elements widely used in offshore industry. Subsea operations are very expensive; optimizing time and money resources are the core factors driving innovation in the subsea metrology industry. In this study, the authors investigate the use of state-of-art vision-based algorithms, i.e. ORB-SLAM2 and Visual Odometry, as a navigation tool to assist and control a Remotely Operated Vehicle (ROV) while performing subsea metrology operations. In particular, the manuscript will focus on methods for assessing the accuracy of both trajectory and tie points provided by the tested approaches and evaluating whether the preliminary real time reconstruction meets the tolerances defined in typical subsea metrology scenarios.

Given the rise and wide adoption of Structure from Motion (SfM) and Multi View Stereo (MVS) in underwater archaeology, this paper investigates the optimal option for surveying ground control point networks. Such networks are the essential framework for coregistration of photogrammetric 3D models acquired in different epochs, and consecutive archaeological related study and analysis. Above the water, on land, coordinates of ground control points are determined with geodetic methods and are considered often definitive. Other survey works are then derived from by using those coordinates as fixed (being ground control points coordinates considered of much higher precision). For this reason, equipment of proven precision is used with methods that not only compute the most correct values (according to the least squares principle) but also provide numerical measures of their precisions and reliability. Under the water, there are two options for surveying such control networks: trilateration and photogrammetry, with the former being the choice of the majority of archaeological expeditions so far. It has been adopted because of ease of implementation and under the assumption that it is more reliable and precise than photogrammetry.This work aims at investigating the precision of network establishment by both methodologies by comparing them in a typical underwater archaeological site. Photogrammetric data were acquired and analysed, while the trilateration data were simulated under certain assumptions. Direct comparison of standard deviation values of both methodologies reveals a clear advantage of photogrammetry in the vertical (Z) axis and three times better results in horizontal precision.

A key challenge in cultural heritage (CH) sites visualization is to provide models and tools that effectively integrate the content of a CH data with domain-specific knowledge so that the users can query, interpret and consume the visualized information. Moreover, it is important that the intelligent visualization systems are interoperable in the semantic web environment and thus, capable of establishing a methodology to acquire, integrate, analyze, generate and share numeric contents and associated knowledge in human and machine-readable Web. In this paper, we present a model, a methodology and a software Web-tools that support the coupling of the 2D/3D Web representation with the knowledge graph database of Xlendi shipwreck. The Web visualization tools and the knowledge-based techniques are married into a photogrammetry driven ontological model while at the same time, user-friendly web tools for querying and semantic consumption of the shipwreck information are introduced.

This study presents an evaluation of a cheap consumer-grade camera used for modelling a coral reef section. We evaluate the quality of a reconstructed coral reef using GoPro cameras and a high-end camera with data from an actual coral reef dataset. We also investigate components of the processing pipeline (like image quality) separate from the final results. Because our GoPro images suffer from severe chromatic aberration, we apply different image pre-processing steps to improve their quality and show its effects on the reconstructed object points. Bundle adjustment is carried out as free networks in all cases, with a follow-up rigid 3D Helmert transformation onto a geodetic control network, carried out to define the common datum and to remove the bias from the free network results.

Underwater photogrammetry is a well-established technique for measuring and modelling the subaquatic environment in fields ranging from archaeology to marine ecology. While for simple tasks the acquisition and processing of images have become straightforward, applications requiring relative accuracy better then 1:1000 are still considered challenging. This study focuses on the metric evaluation of different off-the-shelf camera systems for making high resolution and high accuracy measurements of coral reefs monitoring through time, where the variations to be measured are in the range of a few centimeters per year. High quality and low-cost systems (reflex and mirrorless vs action cameras, i.e. GoPro) with multiple lenses (prime and zoom), different fields of views (from fisheye to moderate wide angle), pressure housing materials and lens ports (dome and flat) are compared. Tests are repeated at different camera to object distances to investigate distance dependent induced errors and assess the accuracy of the photogrammetrically derived models. An extensive statistical analysis of the different systems is performed and comparisons against reference control point measured through a high precision underwater geodetic network are reported.

Exploration, documentation and mapping of underwater environment is one of the biggest open challenges for science and engineering. Humankind is not naturally designed to operate in water and, despite the enormous technological advancement that offers nowadays unprecedented opportunities, diving and working underwater is still very dangerous, especially in confined spaces such as underwater caves. Great research efforts are currently devoted to underwater autonomous navigation, but available solutions still mainly rely on complex and expensive systems, due to the difficulty of adapting localization and mapping sensors and algorithms suited for terrestrial or aerial applications. However, small and affordable underwater remotely operated vehicles (ROVs) are available, which offer good opportunities for underwater exploration and mapping. This paper focuses on the development of a small, low-cost ROV designed for 3D mapping of underwater environments, like caves. The system is based on a commercially available vehicle, the BluRov2, and relies on the use of up to 12 action cameras (GoPro) mounted on it. A trifocal camera system for underwater real-time visual odometry can also be included. The work describes the photogrammetric procedure developed for the synchronization and calibration of the GoPro cameras and provides a thorough analysis on the achievable results.

An underwater imaging system with camera and lens behind a flat port does not behave as a standard pinhole camera with additional parameters. Indeed, whenever the entrance pupil of the lens is not in contact with the flat port, the standard photogrammetric model is not suited anymore and an extended mathematical model that considers the different media would be required. Therefore, when dealing with flat ports, the use of the classic photogrammetric formulation represents a simplification of the image formation phenomenon, clearly causing a degradation in accuracy. Furthermore, flat ports significantly change the characteristics of the enclosed imaging device and negatively affect the image quality, introducing heavy curvilinear distortions and optical aberrations. With the aim of mitigating the effect of systematic errors introduced by a combination of (i) image quality degradation, induced by the flat ports, and (ii) a non-rigorous modelling of refraction, this paper presents a stochastic model for image observations that penalises those that are more affected by aberrations and departure from the pinhole model. Experiments were carried out at sea and in pools showing that the use of the proposed stochastic model is beneficial for the final accuracy with improvements up to 50 %.

This paper presents a web-based 3D imaging pipeline, namely 3Dnow, that can be used by anyone without the need of installing additional software other than a browser. By uploading a set of images through the web interface, 3Dnow can generate sparse and dense point clouds as well as mesh models. 3D reconstructed models can be downloaded with standard formats or previewed directly on the web browser through an embedded visualisation interface. In addition to reconstructing objects, 3Dnow offers the possibility to evaluate and georeference point clouds. Reconstruction statistics, such as minimum, maximum and average intersection angles, point redundancy and density can also be accessed. The paper describes all features available in the web service and provides an analysis of the computational performance using servers with different GPU configurations.

Ecological studies about marine benthic communities received a major leap from the application of a variety of non-destructive sampling and mapping techniques based on underwater image and video recording. The well-established scientific diving practice consists in the acquisition of single path or ‘round-trip’ over elongated transects, with the imaging device oriented in a nadir looking direction. As it may be expected, the application of automatic image processing procedures to data not specifically acquired for 3D modelling can be risky, especially if proper tools for assessing the quality of the produced results are not employed. This paper, born from an international cooperation, focuses on this topic, which is of great interest for ecological and monitoring benthic studies in Antarctica. Several video footages recorded from different scientific teams in different years are processed with an automatic photogrammetric procedure and salient statistical features are reported to critically analyse the derived results. As expected, the inclusion of oblique images from additional lateral strips may improve the expected accuracy in the object space, without altering too much the current video recording practices.

Creating 3-dimensional (3D) models of underwater scenes has become a common approach for monitoring coral reef changes and its structural complexity. Also in underwater archeology, 3D models are often created using underwater optical imagery. In this paper, we focus on the aspect of detecting small changes in the coral reef using a multi-temporal photogrammetric modelling approach, which requires a high quality control network. We show that the quality of a good geodetic network limits the direct change detection, i.e., without any further registration process. As the photogrammetric accuracy is expected to exceed the geodetic network accuracy by at least one order of magnitude, we suggest to do a fine registration based on a number of signalized points. This work is part of the Moorea Island Digital Ecosystem Avatar (IDEA) project that has been initiated in 2013 by a group of international researchers (https://mooreaidea.ethz.ch/).

In this paper we investigate how the residuals in bundle adjustment can be split into a composition of simple functions. According to the chain rule, the Jacobian (linearisation) of the residual can be formed as a product of the Jacobians of the individual steps. When implemented, this enables a modularisation of the computation of the bundle adjustment residuals and Jacobians where each component has limited responsibility. This enables simple replacement of components to e.g. implement different projection or rotation models by exchanging a module. The technique has previously been used to implement bundle adjustment in the open-source package DBAT (Börlin and Grussenmeyer, 2013) based on the Photogrammetric and Computer Vision interpretations of Brown (1971) lens distortion model. In this paper, we applied the technique to investigate how affine distortions can be used to model the projection of a tilt-shift lens. Two extended distortion models were implemented to test the hypothesis that the ordering of the affine and lens distortion steps can be changed to reduce the size of the residuals of a tilt-shift lens calibration. Results on synthetic data confirm that the ordering of the affine and lens distortion steps matter and is detectable by DBAT. However, when applied to a real camera calibration data set of a tilt-shift lens, no difference between the extended models was seen. This suggests that the tested hypothesis is false and that other effects need to be modelled to better explain the projection. The relatively low implementation effort that was needed to generate the models suggest that the technique can be used to investigate other novel projection models in photogrammetry, including modelling changes in the 3D geometry to better understand the tilt-shift lens.

The paper presents an investigation about the combination of multispectral and 3D imaging aiming at the analysis of the condition and preservation of an ancient vase. Visible-reflected (VIS) and -induced luminescence (UVL) images are mapped to 3D models produced with image- and range-based 3D modelling techniques. The case study is an Attic vase, part of the pottery collection of the Landesmuseum Rudolfinum (Carinthia, Austria) and temporarily stored in the Institute of Archaeology of the University of Graz, Austria. The aim of this study is to exploit the added-value provided by mapping multispectral imaging onto 3D geometry for a comprehensive knowledge of the condition of a restored Cultural Heritage (CH) item.

3D digitization of heritage artefacts, reverse engineering of industrial components or rapid prototyping-driven design are key topics today. Indeed, millions of archaeological finds all over the world need to be surveyed in 3D either to allow convenient investigations by researchers or because they are inaccessible to visitors and scientists or, unfortunately, because they are seriously endangered by wars and terrorist attacks. On the other hand, in case of industrial and design components there is often the need of deformation analyses or physical replicas starting from reality-based 3D digitisations. The paper is aligned with these needs and presents the realization of the ORION (arduinO Raspberry pI rOtating table for image based 3D recostructioN) prototype system, with its hardware and software components, providing critical insights about its modular design. ORION is an image-based 3D reconstruction system based on automated photogrammetric acquisitions and processing. The system is being developed under a collaborative educational project between FBK Trento, the University of Trento and internship programs with high school in the Trentino province (Italy).

The paper presents a collaborative image-based 3D reconstruction pipeline to perform image acquisition with a smartphone and geometric 3D reconstruction on a server during concurrent or disjoint acquisition sessions. Images are selected from the video feed of the smartphone’s camera based on their quality and novelty. The smartphone’s app provides on-the-fly reconstruction feedback to users co-involved in the acquisitions. The server is composed of an incremental SfM algorithm that processes the received images by seamlessly merging them into a single sparse point cloud using bundle adjustment. Dense image matching algorithm can be lunched to derive denser point clouds. The reconstruction details, experiments and performance evaluation are presented and discussed.

Multispectral imaging is a widely used remote sensing technique, whose applications range from agriculture to environmental monitoring, from food quality check to cultural heritage diagnostic. A variety of multispectral imaging sensors are available on the market, many of them designed to be mounted on different platform, especially small drones. This work focuses on the geometric and radiometric characterization of a brand-new, lightweight, low-cost multispectral camera, called MAIA. The MAIA camera is equipped with nine sensors, allowing for the acquisition of images in the visible and near infrared parts of the electromagnetic spectrum. Two versions are available, characterised by different set of band-pass filters, inspired by the sensors mounted on the WorlView-2 and Sentinel2 satellites, respectively. The camera details and the developed procedures for the geometric calibrations and radiometric correction are presented in the paper.

The VAST (valorisation of history and landscape) project (http://vast.fbk.eu/) was part of the initiatives promoted by the Autonomous Province of Trento (Italy) for the commemoration of the 100th Anniversary of the First World War (WWI) outbreak. The project was primarily aimed to document and promote, through 3D digitization approaches and communication material, the memory of sites, theatre of the world conflict. The Italian Trento’s province had been under the Austro–Hungarian Empire until the end of the WWI, during which represented a crucial and bloody war front between the Austrian and Italian territories. The region was constellated of military fortresses, trenches and tunnels, most of them now ruined and at risk to slowly disappear. 3D surveying and modelling techniques have been exploited to produce 3D digital models of structures and objects, along with virtual tours, communication material and a WebGIS of the area. All the products are available on the web for valorisation, educational and communication purposes.

The paper reports some comparisons between commercial software able to automatically process image datasets for 3D reconstruction purposes. The main aspects investigated in the work are the capability to correctly orient large sets of image of complex environments, the metric quality of the results, replicability and redundancy. Different datasets are employed, each one featuring a diverse number of images, GSDs at cm and mm resolutions, and ground truth information to perform statistical analyses of the 3D results. A summary of (photogrammetric) terms is also provided, in order to provide rigorous terms of reference for comparisons and critical analyses.

Recent developments of 3D technologies and tools have increased availability and relevance of 3D data (from 3D points to complete city models) in the geospatial and geo-information domains. Nevertheless, the potential of 3D data is still underexploited and mainly confined to visualization purposes. Therefore, the major challenge today is to create automatic procedures that make best use of available technologies and data for the benefits and needs of public administrations (PA) and national mapping agencies (NMA) involved in “smart city” applications. The paper aims to demonstrate a step forward in this process by presenting the results of the SENECA project (Smart and SustaiNablE City from Above – http://seneca.fbk.eu). State-of-the-art processing solutions are investigated in order to (i) efficiently exploit the photogrammetric workflow (aerial triangulation and dense image matching), (ii) derive topologically and geometrically accurate 3D geo-objects (i.e. building models) at various levels of detail and (iii) link geometries with non-spatial information within a 3D geo-database management system accessible via web-based client. The developed methodology is tested on two case studies, i.e. the cities of Trento (Italy) and Graz (Austria). Both spatial (i.e. nadir and oblique imagery) and non-spatial (i.e. cadastral information and building energy consumptions) data are collected and used as input for the project workflow, starting from 3D geometry capture and modelling in urban scenarios to geometry enrichment and management within a dedicated webGIS platform.

Accurate 3D city models represent an important source of geospatial information to support various “smart city” applications, such as space management, energy assessment, 3D cartography, noise and pollution mapping as well as disaster management. Even though remarkable progress has been made in recent years, there are still many open issues, especially when it comes to the 3D modelling of complex urban scenarios like historical and densely-built city centres featuring narrow streets and non-conventional building shapes. Most approaches introduce strong building priors/constraints on symmetry and roof typology that penalize urban environments having high variations of roof shapes. Furthermore, although oblique photogrammetry is rapidly maturing, the use of slanted views for façade reconstruction is not completely included in the reconstruction pipeline of state-of-the-art software. This paper aims to investigate state-of-the-art methods for 3D building modelling in complex urban scenarios with the support of oblique airborne images. A reconstruction approach based on roof primitives fitting is tested. Oblique imagery is then exploited to support the manual editing of the generated building models. At the same time, mobile mapping data are collected at cm resolution and then integrated with the aerial ones. All approaches are tested on the historical city centre of Bergamo (Italy).

During the last two decades we have witnessed great improvements in ICT hardware and software technologies. Three-dimensional content is starting to become commonplace now in many applications. Although for many years 3D technologies have been used in the generation of assets by researchers and experts, nowadays these tools are starting to become commercially available to every citizen. This is especially the case for smartphones, that are powerful enough and sufficiently widespread to perform a huge variety of activities (e.g. paying, calling, communication, photography, navigation, localization, etc.), including just very recently the possibility of running 3D reconstruction pipelines. The REPLICATE project is tackling this particular issue, and it has an ambitious vision to enable ubiquitous 3D creativity via the development of tools for mobile 3D-assets generation on smartphones/tablets. This article presents the REPLICATE project’s concept and some of the ongoing activities, with particular attention being paid to advances made in the first year of work. Thus the article focuses on the system architecture definition, selection of optimal frames for 3D cloud reconstruction, automated generation of sparse and dense point clouds, mesh modelling techniques and post-processing actions. Experiments so far were concentrated on indoor objects and some simple heritage artefacts, however, in the long term we will be targeting a larger variety of scenarios and communities.

Underwater photogrammetry, like its counterpart in 'air', has gained an increasing diffusion thanks to the availability of easy-to-use, fast and often quite inexpensive software applications. Moreover, underwater equipment that allows the use of digital cameras normally designed to work in air also in water are largely available. However, for assuring accurate and reliable 3D modelling results a profound knowledge of the employed devices as well as physical and geometric principle is even more crucial than in air. This study aims to take a step forward in understanding the effect of underwater ports in front of the photographic lens. In particular, the effect of dome or flat ports on image quality in 3D modelling applications is investigated. Experiments conducted in a semi submerged indust rial structure show that the tested flat port performs worse than the dome, providing higher image residuals and lower precision and accuracy in object space. A significant different quality per colour channel is also observed and its influence on achievable processing results is discussed.

In the last years, cardiovascular diagnosis, surgical planning and intervention have taken advantages from 3D modelling and rapid prototyping techniques. The starting data for the whole process is represented by medical imagery, in particular, but not exclusively, computed tomography (CT) or multi-slice CT (MCT) and magnetic resonance imaging (MRI). On the medical imagery, regions of interest, i.e. heart chambers, valves, aorta, coronary vessels, etc., are segmented and converted into 3D models, which can be finally converted in physical replicas through 3D printing procedure. In this work, an overview on modern approaches for automatic and semiautomatic segmentation of medical imagery for 3D surface model generation is provided. The issue of accuracy check of surface models is also addressed, together with the critical aspects of converting digital models into physical replicas through 3D printing techniques. A patient-specific 3D modelling and printing procedure (Figure 1), for surgical planning in case of complex heart diseases was developed. The procedure was applied to two case studies, for which MCT scans of the chest are available. In the article, a detailed description on the implemented patient-specific modelling procedure is provided, along with a general discussion on the potentiality and future developments of personalized 3D modelling and printing for surgical planning and surgeons practice.

Photogrammetry is currently facing some challenges and changes mainly related to automation, ubiquitous processing and variety of applications. Within an ISPRS Scientific Initiative a team of researchers from USAL, UCLM, FBK and UNIBO have developed an open photogrammetric tool, called GRAPHOS (inteGRAted PHOtogrammetric Suite). GRAPHOS allows to obtain dense and metric 3D point clouds from terrestrial and UAV images. It encloses robust photogrammetric and computer vision algorithms with the following aims: (i) increase automation, allowing to get dense 3D point clouds through a friendly and easy-to-use interface; (ii) increase flexibility, working with any type of images, scenarios and cameras; (iii) improve quality, guaranteeing high accuracy and resolution; (iv) preserve photogrammetric reliability and repeatability. Last but not least, GRAPHOS has also an educational component reinforced with some didactical explanations about algorithms and their performance. The developments were carried out at different levels: GUI realization, image pre-processing, photogrammetric processing with weight parameters, dataset creation and system evaluation. The paper will present in detail the developments of GRAPHOS with all its photogrammetric components and the evaluation analyses based on various image datasets. GRAPHOS is distributed for free for research and educational needs.

Despite being perceived as interchangeable when properly applied, close-range photogrammetry and range imaging have both their pros and limitations that can be overcome using suitable procedures. Even if the two techniques have been frequently cross-compared, critical analysis discussing all sub-phases of a complex digitization project are quite rare. Comparisons taking into account the digitization of a cultural masterpiece, such as the Etruscan Sarcophagus of the Spouses (Figure 1) discussed in this paper, are even less common. The final 3D model of the Sarcophagus shows impressive spatial and texture resolution, in the order of tenths of millimetre for both digitization techniques, making it a large 3D digital model even though the physical size of the artwork is quite limited. The paper presents the survey of the Sarcophagus, a late 6th century BC Etruscan anthropoid Sarcophagus. Photogrammetry and laser scanning were used for its 3D digitization in two different times only few days apart from each other. The very short time available for the digitization was a crucial constraint for the surveying operations (due to constraints imposed us by the museum curators). Despite very high-resolution and detailed 3D models have been produced, a metric comparison between the two models shows intrinsic limitations of each technique that should be overcome through suitable onsite metric verification procedures as well as a proper processing workflow.

One of the strongest limiting factors in close range photogrammetry (CRP) is the depth of field (DOF), especially at very small object distance. When using standard digital cameras and lens, for a specific camera – lens combination, the only way to control the extent of the zone of sharp focus in object space is to reduce the aperture of the lens. However, this strategy is often not sufficient; moreover, in many cases it is not fully advisable. In fact, when the aperture is closed down, images lose sharpness because of diffraction. Furthermore, the exposure time must be lowered (susceptibility to vibrations) and the ISO increased (electronic noise may increase). In order to adapt the shape of the DOF to the subject of interest, the Scheimpflug rule is to be applied, requiring that the optical axis must be no longer perpendicular to the image plane. Nowadays, specific lenses exist that allow inclining the optical axis to modify the DOF: they are called tilt-shift lenses. In this paper, an investigation on the applicability of the classic photogrammetric model (pinhole camera coupled with Brown’s distortion model) to these lenses is presented. Tests were carried out in an environmentally controlled metrology laboratory at the National Research Council (NRC) Canada and the results are hereafter described in detail.

The paper presents the first results of an interdisciplinary project related to the 3D documentation, dissemination, valorization and digital access of archeological sites. Beside the mere 3D documentation aim, the project has two goals: (i) to easily explore and share via web references and results of the interdisciplinary work, including the interpretative process and the final reconstruction of the remains; (ii) to promote and valorize archaeological areas using reality-based 3D data and Virtual Reality devices. This method has been verified on the ruins of the archeological site of Pausilypon, a maritime villa of Roman period (Naples, Italy). Using Unity3D, the virtual tour of the heritage site was integrated and enriched with the surveyed 3D data, text documents, CAAD reconstruction hypotheses, drawings, photos, etc. In this way, starting from the actual appearance of the ruins (panoramic images), passing through the 3D digital surveying models and several other historical information, the user is able to access virtual contents and reconstructed scenarios, all in a single virtual, interactive and immersive environment. These contents and scenarios allow to derive documentation and geometrical information, understand the site, perform analyses, see interpretative processes, communicate historical information and valorize the heritage location.

The accuracy of 3D surface reconstruction was compared from image sets of a Metric Test Object taken in an illumination dome by two methods: photometric stereo and improved structure-from-motion (SfM), using point cloud data from a 3D colour laser scanner as the reference. Metrics included pointwise height differences over the digital elevation model (DEM), and 3D Euclidean differences between corresponding points. The enhancement of spatial detail was investigated by blending high frequency detail from photometric normals, after a Poisson surface reconstruction, with low frequency detail from a DEM derived from SfM.

Underwater photogrammetry using consumer grade photographic equipment can be feasible for different applications, e.g. archaeology, biology, industrial inspections, etc. The use of a camera underwater can be very different from its terrestrial use due to the optical phenomena involved. The presence of the water and camera pressure housing in front of the camera act as additional optical elements. Spherical dome ports are difficult to manufacture and consequently expensive but at the same time they are the most useful for underwater photogrammetry as they keep the main geometric characteristics of the lens unchanged. Nevertheless, the manufacturing and alignment of dome port pressure housing components can be the source of unexpected changes of radial and decentring distortion, source of systematic errors that can influence the final 3D measurements. The paper provides a brief introduction of underwater optical phenomena involved in underwater photography, then presents the main differences between flat and dome ports to finally discuss the effect of manufacturing on 3D measurements in two case studies.