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The topic of underwater (UW) image colour correction and restoration has gained significant scientific interest in the last couple of decades. There are a vast number of disciplines, from marine biology to archaeology, that can and need to utilise the true information of the UW environment. Based on that, a significant number of scientists have contributed to the topic of UW image colour correction and restoration. In this paper, we try to make an unbiased and extensive review of some of the most significant contributions from the last 15 years. After considering the optical properties of water, as well as light propagation and haze that is caused by it, the focus is on the different methods that exist in the literature. The criteria for which most of them were designed, as well as the quality evaluation used to measure their effectiveness, are underlined.
Marinos Vlachos; Dimitrios Skarlatos. An Extensive Literature Review on Underwater Image Colour Correction. Sensors 2021, 21, 5690 .
AMA StyleMarinos Vlachos, Dimitrios Skarlatos. An Extensive Literature Review on Underwater Image Colour Correction. Sensors. 2021; 21 (17):5690.
Chicago/Turabian StyleMarinos Vlachos; Dimitrios Skarlatos. 2021. "An Extensive Literature Review on Underwater Image Colour Correction." Sensors 21, no. 17: 5690.
The increasing need for accurate bathymetric mapping is essential for a plethora of offshore activities. Even though aerial image datasets through Structure from Motion (SfM) and Multi-View Stereo (MVS) techniques can provide a low-cost alternative compared to LiDAR and SONAR, offering additionally, important visual information, water refraction poses significant obstacles in delivering accurate bathymetry. In this article, the generation of manned and unmanned airborne synthetic datasets of dry and water covered areas is presented. These data are used to train models for correcting the geometric effects of refraction on real-world image-based point clouds and aerial images. Based on a thorough evaluation, important improvements are presented, indicating the increased accuracy and the reduced noise in the point clouds of the derived bathymetric products, meeting also the International Hydrographic Organization’s (IHO) standards.
Panagiotis Agrafiotis; Konstantinos Karantzalos; Andreas Georgopoulos; Dimitrios Skarlatos. Learning from Synthetic Data: Enhancing Refraction Correction Accuracy for Airborne Image-Based Bathymetric Mapping of Shallow Coastal Waters. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science 2021, 1 -19.
AMA StylePanagiotis Agrafiotis, Konstantinos Karantzalos, Andreas Georgopoulos, Dimitrios Skarlatos. Learning from Synthetic Data: Enhancing Refraction Correction Accuracy for Airborne Image-Based Bathymetric Mapping of Shallow Coastal Waters. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science. 2021; ():1-19.
Chicago/Turabian StylePanagiotis Agrafiotis; Konstantinos Karantzalos; Andreas Georgopoulos; Dimitrios Skarlatos. 2021. "Learning from Synthetic Data: Enhancing Refraction Correction Accuracy for Airborne Image-Based Bathymetric Mapping of Shallow Coastal Waters." PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science , no. : 1-19.
The Special Issue “Underwater 3D recording and modelling” is focused on challenges for 3D modeling and ways to overcome them in the underwater environment. Given that existing sensors and algorithms are not optimized, nor present the best possible solutions for the harsh conditions of the submerged environment, new techniques and methods need to be developed. During the last years, we have witnessed groundbreaking technological developments, which allow underwater documentation with unprecedented accuracy and detail. Photogrammetry‐based approaches coupled with virtual and augmented reality (VR/AR) applications are becoming infused in interdisciplinary research in topics such as archeology, biology, industry.
Dimitrios Skarlatos; Fabio Bruno; Fabio Menna; Erica Nocerino. Editorial for Underwater 3D Recording & Modelling. Remote Sensing 2021, 13, 665 .
AMA StyleDimitrios Skarlatos, Fabio Bruno, Fabio Menna, Erica Nocerino. Editorial for Underwater 3D Recording & Modelling. Remote Sensing. 2021; 13 (4):665.
Chicago/Turabian StyleDimitrios Skarlatos; Fabio Bruno; Fabio Menna; Erica Nocerino. 2021. "Editorial for Underwater 3D Recording & Modelling." Remote Sensing 13, no. 4: 665.
This paper presents a combined subjective and objective evaluation of an application mixing interactive virtual reality (VR) experience with 360° storytelling. The hypothesis that the modern immersive archaeological VR application presenting cultural heritage from a submerged site would sustain high levels of presence, immersion, and general engagement was leveraged in the investigation of the user experience with both the subjective (questionnaires) and the objective (neurophysiological recording of the brain signals using electroencephalography (EEG)) evaluation methods. Participants rated the VR experience positively in the questionnaire scales for presence, immersion, and subjective judgement. High positive rating concerned also the psychological states linked to the experience (engagement, emotions, and the state of flow), and the experience was mostly free from difficulties linked to the accustomization to the VR technology (technology adoption to the head-mounted display and controllers, VR sickness). EEG results are in line with past studies examining brain responses to virtual experiences, while new results in the beta band suggest that EEG is a viable tool for future studies of presence and immersion in VR.
Filip Škola; Selma Rizvić; Marco Cozza; Loris Barbieri; Fabio Bruno; Dimitrios Skarlatos; Fotis Liarokapis. Virtual Reality with 360-Video Storytelling in Cultural Heritage: Study of Presence, Engagement, and Immersion. Sensors 2020, 20, 5851 .
AMA StyleFilip Škola, Selma Rizvić, Marco Cozza, Loris Barbieri, Fabio Bruno, Dimitrios Skarlatos, Fotis Liarokapis. Virtual Reality with 360-Video Storytelling in Cultural Heritage: Study of Presence, Engagement, and Immersion. Sensors. 2020; 20 (20):5851.
Chicago/Turabian StyleFilip Škola; Selma Rizvić; Marco Cozza; Loris Barbieri; Fabio Bruno; Dimitrios Skarlatos; Fotis Liarokapis. 2020. "Virtual Reality with 360-Video Storytelling in Cultural Heritage: Study of Presence, Engagement, and Immersion." Sensors 20, no. 20: 5851.
There are different ways of discovering underwater archaeological sites. This paper presents search techniques for discovering artefacts in the form of two different educational games. The first one is a classical serious game that assesses two maritime archaeological methods for search and discovering artefacts including circular and compass search. Evaluation results with 30 participants indicated that the circular search method is the most appropriate one. Based on these results, an immersive virtual reality search and discovery simulation was implemented. To educate the users about underwater site formation process digital storytelling videos were used when an artefact is discovered.
Fotis Liarokapis; Iveta Vidová; Selma Rizvić; Stella Demesticha; Dimitrios Skarlatos. Underwater Search and Discovery: From Serious Games to Virtual Reality. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 178 -197.
AMA StyleFotis Liarokapis, Iveta Vidová, Selma Rizvić, Stella Demesticha, Dimitrios Skarlatos. Underwater Search and Discovery: From Serious Games to Virtual Reality. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; ():178-197.
Chicago/Turabian StyleFotis Liarokapis; Iveta Vidová; Selma Rizvić; Stella Demesticha; Dimitrios Skarlatos. 2020. "Underwater Search and Discovery: From Serious Games to Virtual Reality." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 178-197.
The global breeding population of Eleonora’s Falcon (Falco eleonorae) is distributed from the Canary Islands in the west, across the Mediterranean Sea, to Cyprus in the east. The remoteness of nesting colonies, which are predominantly located on sea cliffs and islets, renders breeding success estimation a challenging task, requiring a composite approach to assess each of the breeding stages. Early estimates of the breeding success of Eleonora’s Falcon suggested that the Akrotiri colony in Cyprus had the lowest breeding success among all the colonies throughout the species’ breeding range, at a level seemingly unsustainable, suggesting the colony might have been in danger of gradual extinction. Here we use a diversity of survey methods including boat, ground, and aerial surveys, with the incorporation of photography and photogrammetry, to reassess the breeding success and the effect of nest characteristics on the Eleonora’s Falcon breeding population in Cyprus. During a 6-yr study, we found that Cyprus hosts ~138 ± 8 breeding pairs and that breeding success equals 1.54 ± 0.85 fledglings per breeding pair, and thus is considerably higher than previous estimates. In addition, by analyzing temporal variation in breeding and nest characteristics, we found that early breeding and reuse of nests positively influence breeding success, but physical nest characteristics have a limited effect on colony productivity. The range of survey methods employed, as well as the array of photography techniques utilized, enhanced the efficiency and accuracy of this study, allowing us to overcome the challenge of inaccessibility of nesting cliffs.
Thomas G Hadjikyriakou; Nikolaos Kassinis; Dimitrios Skarlatos; Pantelis Charilaou; Alexander N G Kirschel. Breeding success of Eleonora’s Falcon in Cyprus revisited using survey techniques for cliff-nesting species. Ornithological Applications 2020, 122, 1 .
AMA StyleThomas G Hadjikyriakou, Nikolaos Kassinis, Dimitrios Skarlatos, Pantelis Charilaou, Alexander N G Kirschel. Breeding success of Eleonora’s Falcon in Cyprus revisited using survey techniques for cliff-nesting species. Ornithological Applications. 2020; 122 (4):1.
Chicago/Turabian StyleThomas G Hadjikyriakou; Nikolaos Kassinis; Dimitrios Skarlatos; Pantelis Charilaou; Alexander N G Kirschel. 2020. "Breeding success of Eleonora’s Falcon in Cyprus revisited using survey techniques for cliff-nesting species." Ornithological Applications 122, no. 4: 1.
Land cover classification with the focus on chlorophyll-rich vegetation detection plays an important role in urban growth monitoring and planning, autonomous navigation, drone mapping, biodiversity conservation, etc. Conventional approaches usually apply the normalized difference vegetation index (NDVI) for vegetation detection. In this paper, we investigate the performance of deep learning and conventional methods for vegetation detection. Two deep learning methods, DeepLabV3+ and our customized convolutional neural network (CNN) were evaluated with respect to their detection performance when training and testing datasets originated from different geographical sites with different image resolutions. A novel object-based vegetation detection approach, which utilizes NDVI, computer vision, and machine learning (ML) techniques, is also proposed. The vegetation detection methods were applied to high-resolution airborne color images which consist of RGB and near-infrared (NIR) bands. RGB color images alone were also used with the two deep learning methods to examine their detection performances without the NIR band. The detection performances of the deep learning methods with respect to the object-based detection approach are discussed and sample images from the datasets are used for demonstrations.
Bulent Ayhan; Chiman Kwan; Bence Budavari; Liyun Kwan; Yan Lu; Daniel Perez; Jiang Li; Dimitrios Skarlatos; Marinos Vlachos. Vegetation Detection Using Deep Learning and Conventional Methods. Remote Sensing 2020, 12, 2502 .
AMA StyleBulent Ayhan, Chiman Kwan, Bence Budavari, Liyun Kwan, Yan Lu, Daniel Perez, Jiang Li, Dimitrios Skarlatos, Marinos Vlachos. Vegetation Detection Using Deep Learning and Conventional Methods. Remote Sensing. 2020; 12 (15):2502.
Chicago/Turabian StyleBulent Ayhan; Chiman Kwan; Bence Budavari; Liyun Kwan; Yan Lu; Daniel Perez; Jiang Li; Dimitrios Skarlatos; Marinos Vlachos. 2020. "Vegetation Detection Using Deep Learning and Conventional Methods." Remote Sensing 12, no. 15: 2502.
The global breeding population of Eleonora’s falcon is distributed from the Canary Islands in the west, across the Mediterranean Sea, to Cyprus in the east. The remoteness of nesting colonies, which are predominantly located on sea cliffs and islets, renders breeding success estimation a challenging task, requiring a composite approach to assess each of the breeding stages. Early estimates of the breeding success of Eleonora’s falcon suggested that Akrotiri colony in Cyprus had the lowest breeding success among all the colonies throughout the species’ breeding range, at a level seemingly unsustainable, suggesting the colony might have been in danger of gradual extinction. Here we use a diversity of survey methods using boat, ground and aerial surveys, with the incorporation of photography and photogrammetry, to reassess the breeding success and the effect of nest characteristics on the Eleonora’s falcon breeding population in Cyprus. During a six-year study, we found that Cyprus hosts ~138 ± 8 breeding pairs and that breeding success equals 1.54 ± 0.85 fledglings per breeding pair, thus considerably higher than previous estimates. In addition, by analyzing temporal variation in breeding and nest characteristics, we found that early breeding and reuse of nests positively influence breeding success, but physical nest characteristics have a limited effect on colony productivity. The range of survey methods employed, as well as the array of photography techniques utilized, highly enhanced the efficiency and accuracy of this study, allowing us to overcome the challenge of inaccessibility of nesting cliffs.
Thomas G. Hadjikyriakou; Nikolaos Kassinis; Dimitrios Skarlatos; Pantelis Charilaou; Alexander N. G. Kirschel. Breeding success of Eleonora’s falcon (Falco eleonorae) in Cyprus revisited using survey techniques for cliff-nesting species. 2020, 1 .
AMA StyleThomas G. Hadjikyriakou, Nikolaos Kassinis, Dimitrios Skarlatos, Pantelis Charilaou, Alexander N. G. Kirschel. Breeding success of Eleonora’s falcon (Falco eleonorae) in Cyprus revisited using survey techniques for cliff-nesting species. . 2020; ():1.
Chicago/Turabian StyleThomas G. Hadjikyriakou; Nikolaos Kassinis; Dimitrios Skarlatos; Pantelis Charilaou; Alexander N. G. Kirschel. 2020. "Breeding success of Eleonora’s falcon (Falco eleonorae) in Cyprus revisited using survey techniques for cliff-nesting species." , no. : 1.
Underwater Cultural Heritage (CH) sites are widely spread; from ruins in coastlines up to shipwrecks in deep. The documentation and preservation of this heritage is an obligation of the mankind, dictated also by the international treaties like the Convention on the Protection of the Underwater Cultural Heritage which fosters the use of “non-destructive techniques and survey methods in preference over the recovery of objects”. However, submerged CH lacks in protection and monitoring in regards to the land CH and nowadays recording and documenting, for digital preservation as well as dissemination through VR to wide public, is of most importance. At the same time, it is most difficult to document it, due to inherent restrictions posed by the environment. In order to create high detailed textured 3D models, optical sensors and photogrammetric techniques seems to be the best solution. This chapter discusses critical aspects of all phases of image based underwater 3D reconstruction process, from data acquisition and data preparation using colour restoration and colour enhancement algorithms to Structure from Motion (SfM) and Multi-View Stereo (MVS) techniques to produce an accurate, precise and complete 3D model for a number of applications.
Dimitrios Skarlatos; Panagiotis Agrafiotis. Image-Based Underwater 3D Reconstruction for Cultural Heritage: From Image Collection to 3D. Critical Steps and Considerations. Movement, Time, Technology, and Art 2020, 141 -158.
AMA StyleDimitrios Skarlatos, Panagiotis Agrafiotis. Image-Based Underwater 3D Reconstruction for Cultural Heritage: From Image Collection to 3D. Critical Steps and Considerations. Movement, Time, Technology, and Art. 2020; ():141-158.
Chicago/Turabian StyleDimitrios Skarlatos; Panagiotis Agrafiotis. 2020. "Image-Based Underwater 3D Reconstruction for Cultural Heritage: From Image Collection to 3D. Critical Steps and Considerations." Movement, Time, Technology, and Art , no. : 141-158.
Although aerial image-based bathymetric mapping can provide, unlike acoustic or LiDAR (Light Detection and Ranging) sensors, both water depth and visual information, water refraction poses significant challenges for accurate depth estimation. In order to tackle this challenge, we propose an image correction methodology, which first exploits recent machine learning procedures that recover depth from image-based dense point clouds and then corrects refraction on the original imaging dataset. This way, the structure from motion (SfM) and multi-view stereo (MVS) processing pipelines are executed on a refraction-free set of aerial datasets, resulting in highly accurate bathymetric maps. Performed experiments and validation were based on datasets acquired during optimal sea state conditions and derived from four different test-sites characterized by excellent sea bottom visibility and textured seabed. Results demonstrated the high potential of our approach, both in terms of bathymetric accuracy, as well as texture and orthoimage quality.
Panagiotis Agrafiotis; Konstantinos Karantzalos; Andreas Georgopoulos; Dimitrios Skarlatos. Correcting Image Refraction: Towards Accurate Aerial Image-Based Bathymetry Mapping in Shallow Waters. Remote Sensing 2020, 12, 322 .
AMA StylePanagiotis Agrafiotis, Konstantinos Karantzalos, Andreas Georgopoulos, Dimitrios Skarlatos. Correcting Image Refraction: Towards Accurate Aerial Image-Based Bathymetry Mapping in Shallow Waters. Remote Sensing. 2020; 12 (2):322.
Chicago/Turabian StylePanagiotis Agrafiotis; Konstantinos Karantzalos; Andreas Georgopoulos; Dimitrios Skarlatos. 2020. "Correcting Image Refraction: Towards Accurate Aerial Image-Based Bathymetry Mapping in Shallow Waters." Remote Sensing 12, no. 2: 322.
Fabio Bruno; Loris Barbieri; Marino Mangeruga; Marco Cozza; Antonio Lagudi; Jan Čejka; Fotis Liarokapis; Dimitrios Skarlatos. Underwater augmented reality for improving the diving experience in submerged archaeological sites. Ocean Engineering 2019, 190, 1 .
AMA StyleFabio Bruno, Loris Barbieri, Marino Mangeruga, Marco Cozza, Antonio Lagudi, Jan Čejka, Fotis Liarokapis, Dimitrios Skarlatos. Underwater augmented reality for improving the diving experience in submerged archaeological sites. Ocean Engineering. 2019; 190 ():1.
Chicago/Turabian StyleFabio Bruno; Loris Barbieri; Marino Mangeruga; Marco Cozza; Antonio Lagudi; Jan Čejka; Fotis Liarokapis; Dimitrios Skarlatos. 2019. "Underwater augmented reality for improving the diving experience in submerged archaeological sites." Ocean Engineering 190, no. : 1.
The determination of accurate bathymetric information is a key element for near offshore activities; hydrological studies, such as coastal engineering applications, sedimentary processes, hydrographic surveying, archaeological mapping and biological research. Through structure from motion (SfM) and multi-view-stereo (MVS) techniques, aerial imagery can provide a low-cost alternative compared to bathymetric LiDAR (Light Detection and Ranging) surveys, as it offers additional important visual information and higher spatial resolution. Nevertheless, water refraction poses significant challenges on depth determination. Till now, this problem has been addressed through customized image-based refraction correction algorithms or by modifying the collinearity equation. In this article, in order to overcome the water refraction errors in a massive and accurate way, we employ machine learning tools, which are able to learn the systematic underestimation of the estimated depths. In particular, an SVR (support vector regression) model was developed, based on known depth observations from bathymetric LiDAR surveys, which is able to accurately recover bathymetry from point clouds derived from SfM-MVS procedures. Experimental results and validation were based on datasets derived from different test-sites, and demonstrated the high potential of our approach. Moreover, we exploited the fusion of LiDAR and image-based point clouds towards addressing challenges of both modalities in problematic areas.
Panagiotis Agrafiotis; Dimitrios Skarlatos; Andreas Georgopoulos; Konstantinos Karantzalos. DepthLearn: Learning to Correct the Refraction on Point Clouds Derived from Aerial Imagery for Accurate Dense Shallow Water Bathymetry Based on SVMs-Fusion with LiDAR Point Clouds. Remote Sensing 2019, 11, 2225 .
AMA StylePanagiotis Agrafiotis, Dimitrios Skarlatos, Andreas Georgopoulos, Konstantinos Karantzalos. DepthLearn: Learning to Correct the Refraction on Point Clouds Derived from Aerial Imagery for Accurate Dense Shallow Water Bathymetry Based on SVMs-Fusion with LiDAR Point Clouds. Remote Sensing. 2019; 11 (19):2225.
Chicago/Turabian StylePanagiotis Agrafiotis; Dimitrios Skarlatos; Andreas Georgopoulos; Konstantinos Karantzalos. 2019. "DepthLearn: Learning to Correct the Refraction on Point Clouds Derived from Aerial Imagery for Accurate Dense Shallow Water Bathymetry Based on SVMs-Fusion with LiDAR Point Clouds." Remote Sensing 11, no. 19: 2225.
Augmented reality can be deployed in various application domains, such as enhancing human vision, manufacturing, medicine, military, entertainment, and archeology. One of the least explored areas is the underwater environment. The main benefit of augmented reality in these environments is that it can help divers navigate to points of interest or present interesting information about archaeological and touristic sites (e.g., ruins of buildings, shipwrecks). However, the harsh sea environment affects computer vision algorithms and complicates the detection of objects, which is essential for augmented reality. This paper presents a new algorithm for the detection of fiducial markers that is tailored to underwater environments. It also proposes a method that generates synthetic images with such markers in these environments. This new detector is compared with existing solutions using synthetic images and images taken in the real world, showing that it performs better than other detectors: it finds more markers than faster algorithms and runs faster than robust algorithms that detect the same amount of markers.
Jan Čejka; Fabio Bruno; Dimitrios Skarlatos; Fotis Liarokapis. Detecting Square Markers in Underwater Environments. Remote Sensing 2019, 11, 459 .
AMA StyleJan Čejka, Fabio Bruno, Dimitrios Skarlatos, Fotis Liarokapis. Detecting Square Markers in Underwater Environments. Remote Sensing. 2019; 11 (4):459.
Chicago/Turabian StyleJan Čejka; Fabio Bruno; Dimitrios Skarlatos; Fotis Liarokapis. 2019. "Detecting Square Markers in Underwater Environments." Remote Sensing 11, no. 4: 459.
The main idea of this particular study was to validate if the new FOVEON technology implemented by sigma cameras can provide better overall results and outperform the traditional Bayer pattern sensor cameras regarding the radiometric information that records as well as the photogrammetric point cloud quality that can provide. Based on that, the scope of this paper is separated into two evaluations. First task is to evaluate the quality of information reconstructed during de-mosaicking step for Bayer pattern cameras by detecting potential additional colour distortion added during the de-mosaicking step, and second task is the geometric comparisons of point clouds generated by the photos by Bayer and FOVEON sensors against a reference point cloud. The first phase of the study is done using various de-mosaicking algorithms to process various artificial Bayern pattern images and then compare them with reference FOVEON images. The second phase of the study is carried on by reconstructing 3D point clouds of the same objects captured by a Bayer and a FOVEON sensor respectively and then comparing the various point clouds with a reference one, generated by a structured light hand-held scanner. The comparison is separated into two parts, where initially we evaluate five separate point clouds (RGB, Gray, Red, Green, Blue) for each camera sensor per site and then a second comparison is evaluated on colour classified RGB point cloud segments.
M. Vlachos; D. Skarlatos; P. Bodin. FOVEON VS BAYER: COMPARISON OF 3D RECONSTRUCTION PERFORMANCES. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2019, XLII-2/W9, 755 -761.
AMA StyleM. Vlachos, D. Skarlatos, P. Bodin. FOVEON VS BAYER: COMPARISON OF 3D RECONSTRUCTION PERFORMANCES. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2019; XLII-2/W9 ():755-761.
Chicago/Turabian StyleM. Vlachos; D. Skarlatos; P. Bodin. 2019. "FOVEON VS BAYER: COMPARISON OF 3D RECONSTRUCTION PERFORMANCES." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W9, no. : 755-761.
Throughout the history of the Mediterranean region, seafaring and trading played a significant role in the interaction between the cultures and people in the area. In order to engage the general public in learning about maritime cultural heritage we have designed and developed a serious game incorporating geospatially analyzed data from open GIS archaeological maritime sources, and archaeological data resulting from shipwreck excavations. We present a second prototype of the seafaring serious game, and discuss the results of an evaluation which involved a large multi-site user study with participants from three continents. More specifically, we present the evaluation of “The Seafarers” a strategy-based game which integrates knowledge from multiple disciplines in order to educate the user through playing. A first prototype was reported in Philbin-Briscoe et al. (2017) where an expert-user evaluation of the usability and the effectiveness of the game in terms of the learning objectives was performed. In this paper, we present how the outcomes of the evaluation of the first prototype “The Seafarers – 1” by expert-users were used in the redesign and development of the game mechanics for the second prototype “The Seafarers-2”. We then present our methodology for evaluating the game with respect to the game objective of engagement in learning about maritime cultural heritage, seafaring and trading in particular. Specifically, the evaluation was to test the hypothesis that game playing allows for more engaged learning thus improving longer-term knowledge retention. The evaluation was conducted in two phases and includes a pilot study, followed by a multi-site, multi-continent user-study involving a large number of participants. We analyze the results of the user evaluation and discuss the outcomes. This work is part of the EU-funded project iMareCulture and involves truly multi-continental, multi-institutional and multi-disciplinary cooperation – civil engineers and archaeologists from Cyprus, Human Computer Interaction (HCI) experts and Educationists from Bosnia and Herzegovina, Canada, and cultural sociologists and computer scientists from Canada.
Charalambos Poullis; Marta Kersten-Oertel; J.Praveen Benjamin; Oliver Philbin-Briscoe; Bart Simon; Dimitra Perissiou; Stella Demesticha; Evangeline Markou; Elias Frentzos; Phaedon Kyriakidis; Dimitrios Skarlatos; Selma Rizvic. Evaluation of “The Seafarers”: A serious game on seaborne trade in the Mediterranean sea during the Classical period. Digital Applications in Archaeology and Cultural Heritage 2019, 12, e00090 .
AMA StyleCharalambos Poullis, Marta Kersten-Oertel, J.Praveen Benjamin, Oliver Philbin-Briscoe, Bart Simon, Dimitra Perissiou, Stella Demesticha, Evangeline Markou, Elias Frentzos, Phaedon Kyriakidis, Dimitrios Skarlatos, Selma Rizvic. Evaluation of “The Seafarers”: A serious game on seaborne trade in the Mediterranean sea during the Classical period. Digital Applications in Archaeology and Cultural Heritage. 2019; 12 ():e00090.
Chicago/Turabian StyleCharalambos Poullis; Marta Kersten-Oertel; J.Praveen Benjamin; Oliver Philbin-Briscoe; Bart Simon; Dimitra Perissiou; Stella Demesticha; Evangeline Markou; Elias Frentzos; Phaedon Kyriakidis; Dimitrios Skarlatos; Selma Rizvic. 2019. "Evaluation of “The Seafarers”: A serious game on seaborne trade in the Mediterranean sea during the Classical period." Digital Applications in Archaeology and Cultural Heritage 12, no. : e00090.
Images obtained in an underwater environment are often affected by colour casting and suffer from poor visibility and lack of contrast. In the literature, there are many enhancement algorithms that improve different aspects of the underwater imagery. Each paper, when presenting a new algorithm or method, usually compares the proposed technique with some alternatives present in the current state of the art. There are no studies on the reliability of benchmarking methods, as the comparisons are based on various subjective and objective metrics. This paper would pave the way towards the definition of an effective methodology for the performance evaluation of the underwater image enhancement techniques. Moreover, this work could orientate the underwater community towards choosing which method can lead to the best results for a given task in different underwater conditions. In particular, we selected five well-known methods from the state of the art and used them to enhance a dataset of images produced in various underwater sites with different conditions of depth, turbidity, and lighting. These enhanced images were evaluated by means of three different approaches: objective metrics often adopted in the related literature, a panel of experts in the underwater field, and an evaluation based on the results of 3D reconstructions.
Marino Mangeruga; Fabio Bruno; Marco Cozza; Panagiotis Agrafiotis; Dimitrios Skarlatos. Guidelines for Underwater Image Enhancement Based on Benchmarking of Different Methods. Remote Sensing 2018, 10, 1652 .
AMA StyleMarino Mangeruga, Fabio Bruno, Marco Cozza, Panagiotis Agrafiotis, Dimitrios Skarlatos. Guidelines for Underwater Image Enhancement Based on Benchmarking of Different Methods. Remote Sensing. 2018; 10 (10):1652.
Chicago/Turabian StyleMarino Mangeruga; Fabio Bruno; Marco Cozza; Panagiotis Agrafiotis; Dimitrios Skarlatos. 2018. "Guidelines for Underwater Image Enhancement Based on Benchmarking of Different Methods." Remote Sensing 10, no. 10: 1652.
Underwater augmented reality is a very challenging task and amongst several issues, one of the most crucial aspects involves real-time tracking. Particles present in water combined with the uneven absorption of light decrease the visibility in the underwater environment. Dehazing methods are used in many areas to improve the quality of digital image data that is degraded by the influence of the environment. This paper describes the visibility conditions affecting underwater scenes and shows existing dehazing techniques that successfully improve the quality of underwater images. Four underwater dehazing methods are selected for evaluation of their capability of improving the success of square marker detection in underwater videos. Two reviewed methods represent approaches of image restoration: Multi-Scale Fusion, and Bright Channel Prior. Another two methods evaluated, the Automatic Color Enhancement and the Screened Poisson Equation, are methods of image enhancement. The evaluation uses diverse test data set to evaluate different environmental conditions. Results of the evaluation show an increased number of successful marker detections in videos pre-processed by dehazing algorithms and evaluate the performance of each compared method. The Screened Poisson method performs slightly better to other methods across various tested environments, while Bright Channel Prior and Automatic Color Enhancement shows similarly positive results.
Marek Žuži; Jan Čejka; Fabio Bruno; Dimitrios Skarlatos; Fotis Liarokapis. Impact of Dehazing on Underwater Marker Detection for Augmented Reality. Frontiers in Robotics and AI 2018, 5, 1 .
AMA StyleMarek Žuži, Jan Čejka, Fabio Bruno, Dimitrios Skarlatos, Fotis Liarokapis. Impact of Dehazing on Underwater Marker Detection for Augmented Reality. Frontiers in Robotics and AI. 2018; 5 ():1.
Chicago/Turabian StyleMarek Žuži; Jan Čejka; Fabio Bruno; Dimitrios Skarlatos; Fotis Liarokapis. 2018. "Impact of Dehazing on Underwater Marker Detection for Augmented Reality." Frontiers in Robotics and AI 5, no. : 1.
Photogrammetry using structure from motion (SfM) techniques has evolved into a powerful tool for a variety of applications. Nevertheless, limits are imposed when two-media photogrammetry is needed, in cases such as submerged archaeological site documentation. Water refraction poses a clear limit on photogrammetric applications, especially when traditional methods and standardized pipelines are followed. This work tries to estimate the error introduced to depth measurements when no refraction correction model is used and proposes an easy to implement methodology in a modern photogrammetric workflow dominated by SfM and multi-view stereo (MVS) techniques. To be easily implemented within current software and workflow, this refraction correction approach is applied at the photo level. Results over two test sites in Cyprus against reference data suggest that despite the assumptions and approximations made the proposed algorithm can reduce the effect of refraction to two times the ground pixel size, regardless of the depth.
Dimitrios Skarlatos; Panagiotis Agrafiotis. A Novel Iterative Water Refraction Correction Algorithm for Use in Structure from Motion Photogrammetric Pipeline. Journal of Marine Science and Engineering 2018, 6, 77 .
AMA StyleDimitrios Skarlatos, Panagiotis Agrafiotis. A Novel Iterative Water Refraction Correction Algorithm for Use in Structure from Motion Photogrammetric Pipeline. Journal of Marine Science and Engineering. 2018; 6 (3):77.
Chicago/Turabian StyleDimitrios Skarlatos; Panagiotis Agrafiotis. 2018. "A Novel Iterative Water Refraction Correction Algorithm for Use in Structure from Motion Photogrammetric Pipeline." Journal of Marine Science and Engineering 6, no. 3: 77.
In this paper, main challenges of underwater photogrammetry in shallow waters are described and analysed. The very short camera to object distance in such cases, as well as buoyancy issues, wave effects and turbidity of the waters are challenges to be resolved. Additionally, the major challenge of all, caustics, is addressed by a new approach for caustics removal (Forbes et al., 2018) which is applied in order to investigate its performance in terms of SfM-MVS and 3D reconstruction results. In the proposed approach the complex problem of removing caustics effects is addressed by classifying and then removing them from the images. We propose and test a novel solution based on two small and easily trainable Convolutional Neural Networks (CNNs). Real ground truth for caustics is not easily available. We show how a small set of synthetic data can be used to train the network and later transfer the learning to real data with robustness to intra-class variation. The proposed solution results in caustic-free images which can be further used for other tasks as may be needed.
P. Agrafiotis; D. Skarlatos; T. Forbes; C. Poullis; M. Skamantzari; A. Georgopoulos. UNDERWATER PHOTOGRAMMETRY IN VERY SHALLOW WATERS: MAIN CHALLENGES AND CAUSTICS EFFECT REMOVAL. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2018, XLII-2, 15 -22.
AMA StyleP. Agrafiotis, D. Skarlatos, T. Forbes, C. Poullis, M. Skamantzari, A. Georgopoulos. UNDERWATER PHOTOGRAMMETRY IN VERY SHALLOW WATERS: MAIN CHALLENGES AND CAUSTICS EFFECT REMOVAL. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2018; XLII-2 ():15-22.
Chicago/Turabian StyleP. Agrafiotis; D. Skarlatos; T. Forbes; C. Poullis; M. Skamantzari; A. Georgopoulos. 2018. "UNDERWATER PHOTOGRAMMETRY IN VERY SHALLOW WATERS: MAIN CHALLENGES AND CAUSTICS EFFECT REMOVAL." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2, no. : 15-22.
Current advancements on photogrammetric software along with affordability and wide spreading of Unmanned Aerial Vehicles (UAV), allow for rapid, timely and accurate 3D modelling and mapping of small to medium sized areas. Although the importance and applications of large format aerial overlaps cameras and photographs in Digital Surface Model (DSM) production and LIDAR data is well documented in literature, this is not the case for UAV photography. Additionally, the main disadvantage of photogrammetry is the inability to map the dead ground (terrain), when we deal with areas that include vegetation. This paper assesses the use of near-infrared imagery captured by small UAV platforms to automatically remove vegetation from Digital Surface Models (DSMs) and obtain a Digital Terrain Model (DTM). Two areas were tested, based on the availability of ground reference points, both under trees and among vegetation, as well as on terrain. In addition, RGB and near-infrared UAV photography was captured and processed using Structure from Motion (SfM) and Multi View Stereo (MVS) algorithms to generate DSMs and corresponding colour and NIR orthoimages with 0.2 m and 0.25 m as pixel size respectively for the two test sites. Moreover, orthophotos were used to eliminate the vegetation from the DSMs using NDVI index, thresholding and masking. Following that, different interpolation algorithms, according to the test sites, were applied to fill in the gaps and created DTMs. Finally, a statistic analysis was made using reference terrain points captured on field, both on dead ground and under vegetation to evaluate the accuracy of the whole process and assess the overall accuracy of the derived DTMs in contrast with the DSMs.
D. Skarlatos; M. Vlachos. VEGETATION REMOVAL FROM UAV DERIVED DSMS, USING COMBINATION OF RGB AND NIR IMAGERY. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2018, IV-2, 255 -262.
AMA StyleD. Skarlatos, M. Vlachos. VEGETATION REMOVAL FROM UAV DERIVED DSMS, USING COMBINATION OF RGB AND NIR IMAGERY. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2018; IV-2 ():255-262.
Chicago/Turabian StyleD. Skarlatos; M. Vlachos. 2018. "VEGETATION REMOVAL FROM UAV DERIVED DSMS, USING COMBINATION OF RGB AND NIR IMAGERY." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2, no. : 255-262.