159 research outputs found
R-CAUSTIC: Rippling CAUSTICs underwater Image dataset
No full text<p><strong>Description</strong></p><p>Rippling caustics seem to be the main factor degrading the underwater RGB image quality and affecting the image- based 3D reconstruction process in very shallow waters. These effects are adversely affecting image matching algorithms by throwing off most of them, leading to less accurate matches and causing issues in the Simultaneous Localization and Mapping (SLAM) based navigation of the Remotely Operated Vehicles (ROV) and Autonomous Underwater Vehicles (AUV) on shallow waters. Also, they are the main cause for dissimilarities in the generated textures and orthoimages. In order to fill the gap in the literature regading underwater rippling caustics imagery with real ground truth and reference images, the first real-world underwater caustics benchmark dataset which contains 1465 underwater images is presented. Together with the RGB imagery, the corresponding generated ground truth images are delivered for facilitating the training and testing of machine learning and deep learning methods for image classification. R-CAUSTIC dataset also provides the necessary data to evaluate, at least to some extent, the performance of 3D reconstruction approaches. Data were acquired using a GoPro Hero 4 Black action camera with image dimensions of 4000 x 3000 pixels, focal length of 2.77mm and pixel size of 1.55μm and a tripod. Action cameras are widely used for underwater image acquisition. The dataset was captured in near-shore underwater sites at depths varying from 0.5 to 2m. No artificial light sources were used. Due to the wind, the turbulent surface of the water created dynamic rippling caustics on the seabed. In total 1465 RGB images were collected, separated in 7 different datasets; five of them containing stereo images, one of them tri-stereo images and one consists of multi-stereo imagery acquired in 7 different camera poses.</p><p> </p><p><strong>Publication</strong></p><p>The paper is availbale in Open Access here: https://ieeexplore.ieee.org/document/10172291</p><p><strong>If you use this dataset please cite it as R-CAUSTIC</strong> [Reference].<br>[Reference]: <strong>P. Agrafiotis, K. Karantzalos and A. Georgopoulos, "Seafloor-Invariant Caustics Removal From Underwater Imagery," in </strong><i><strong>IEEE Journal of Oceanic Engineering</strong></i><strong>, vol. 48, no. 4, pp. 1300-1321, Oct. 2023, doi: 10.1109/JOE.2023.3277168.</strong></p><p>BibTeX:</p><p>@ARTICLE{10172291,
author={Agrafiotis, Panagiotis and Karantzalos, Konstantinos and Georgopoulos, Andreas},
journal={IEEE Journal of Oceanic Engineering},
title={Seafloor-Invariant Caustics Removal From Underwater Imagery},
year={2023},
volume={48},
number={4},
pages={1300-1321},
doi={10.1109/JOE.2023.3277168}}</p><p> </p>
R-CAUSTIC: Rippling CAUSTICs underwater Image dataset
No full text<p> </p>
<h3><strong>Version 2 available! Please make sure to download the latest version of the dataset! <br></strong></h3>
<p> </p>
<p><strong>Description</strong></p>
<p>Rippling caustics seem to be the main factor degrading the underwater RGB image quality and affecting the image- based 3D reconstruction process in very shallow waters. These effects are adversely affecting image matching algorithms by throwing off most of them, leading to less accurate matches and causing issues in the Simultaneous Localization and Mapping (SLAM) based navigation of the Remotely Operated Vehicles (ROV) and Autonomous Underwater Vehicles (AUV) on shallow waters. Also, they are the main cause for dissimilarities in the generated textures and orthoimages. In order to fill the gap in the literature regading underwater rippling caustics imagery with real ground truth and reference images, the first real-world underwater caustics benchmark dataset which contains 1465 underwater images is presented. Together with the RGB imagery, the corresponding generated ground truth images are delivered for facilitating the training and testing of machine learning and deep learning methods for image classification. R-CAUSTIC dataset also provides the necessary data to evaluate, at least to some extent, the performance of 3D reconstruction approaches. Data were acquired using a GoPro Hero 4 Black action camera with image dimensions of 4000 x 3000 pixels, focal length of 2.77mm and pixel size of 1.55μm and a tripod. Action cameras are widely used for underwater image acquisition. The dataset was captured in near-shore underwater sites at depths varying from 0.5 to 2m. No artificial light sources were used. Due to the wind, the turbulent surface of the water created dynamic rippling caustics on the seabed. In total 1465 RGB images were collected, separated in 7 different datasets; five of them containing stereo images, one of them tri-stereo images and one consists of multi-stereo imagery acquired in 7 different camera poses.</p>
<p> </p>
<p><strong>Publication</strong></p>
<p>The paper is availbale in Open Access here: https://ieeexplore.ieee.org/document/10172291</p>
<p><strong>If you use this dataset please cite it as R-CAUSTIC</strong> [Reference].<br>[Reference]: <strong>P. Agrafiotis, K. Karantzalos and A. Georgopoulos, "Seafloor-Invariant Caustics Removal From Underwater Imagery," in </strong><em><strong>IEEE Journal of Oceanic Engineering</strong></em><strong>, vol. 48, no. 4, pp. 1300-1321, Oct. 2023, doi: 10.1109/JOE.2023.3277168.</strong></p>
<p>BibTeX:</p>
<p>@ARTICLE{10172291, author={Agrafiotis, Panagiotis and Karantzalos, Konstantinos and Georgopoulos, Andreas}, journal={IEEE Journal of Oceanic Engineering}, title={Seafloor-Invariant Caustics Removal From Underwater Imagery}, year={2023}, volume={48}, number={4}, pages={1300-1321}, doi={10.1109/JOE.2023.3277168}}</p>
<p> </p>
Precision potential of underwater networks for archaeological excavation through trilateration and photogrammetry
No full textGiven 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
Photogrammetric Modelling of Submerged Structures: Influence of Underwater Environment and Lens Ports on Three-Dimensional (3D) Measurements
No full textCAMERA CONSTANT IN THE CASE OF TWO MEDIA PHOTOGRAMMETRY
No full textRefraction is the main cause of geometric distortions in the case of two media photogrammetry. However, this effect cannot be compensated and corrected by a suitable camera calibration procedure (Georgopoulos and Agrafiotis, 2012). In addition, according to the literature (Lavest et al. 2000), when the camera is underwater, the effective focal length is approximately equal to that in the air multiplied by the refractive index of water. This ratio depends on the composition of the water (salinity, temperature, etc.) and usually ranges from 1.10 to 1.34. It seems, that in two media photogrammetry, the 1.33 factor used for clean water in underwater cases does not apply and the most probable relation of the effective camera constant to the one in air is depending of the percentages of air and water within the total camera-to-object distance. This paper examines this relation in detail, verifies it and develops it through the application of calibration methods using different test fields. In addition the current methodologies for underwater and two-media calibration are mentioned and the problem of two-media calibration is described and analysed
THE EFFECT OF PANSHARPENING ALGORITHMS ON THE RESULTING ORTHOIMAGERY
No full textThis paper evaluates the geometric effects of pansharpening algorithms on automatically generated DSMs and thus on the resulting orthoimagery through a quantitative assessment of the accuracy on the end products. The main motivation was based on the fact that for automatically generated Digital Surface Models, an image correlation step is employed for extracting correspondences between the overlapping images. Thus their accuracy and reliability is strictly related to image quality, while pansharpening may result into lower image quality which may affect the DSM generation and the resulting orthoimage accuracy. To this direction, an iterative methodology was applied in order to combine the process described by Agrafiotis and Georgopoulos (2015) with different pansharpening algorithms and check the accuracy of orthoimagery resulting from pansharpened data. Results are thoroughly examined and statistically analysed. The overall evaluation indicated that the pansharpening process didn’t affect the geometric accuracy of the resulting DSM with a 10m interval, as well as the resulting orthoimagery. Although some residuals in the orthoimages were observed, their magnitude cannot adversely affect the accuracy of the final orthoimagery
Frame delay and loss analysis for video transmission over time-correlated 802.11A/G channels
No full textThis paper presents simulation results for the transmission of unicast MAC frames over 802.11a/g. Fading channel models at various Doppler frequencies are developed to generate time- correlated SNR waveforms. These are then used together with a bit accurate MAC/PHY simulator to estimate the frame loss rate, the transmission delay, and the jitter for a steady flow of transmit frames. Time correlated channels are required to correctly simulate the bursty nature of packet loss in a wireless channel. The Doppler spread is shown to have a strong effect on the performance of the ARQ mechanism in the MAC layer. Delay is computed as the sum of the transmission delay and the accumulated queuing delay in the MAC buffer. Delay and frame loss are compared for time correlated and time uncorrelated fading channels. Compared to the slow fading case, in a fast fading channel fewer retransmissions are required and the end-to-end delay is significantly reduced. When channel conditions are poor the simulated delay and frame loss rate are seriously underestimated when time uncorrelated fading is assumed. To analyze the performance of video codecs, we show that a time correlated channel model must be combined with a dedicated 802.11a/g MAC/PHY simulation.This paper presents simulation results for the transmission of unicast MAC frames over 802.11a/g. Fading channel models at various Doppler frequencies are developed to generate time-correlated SNR waveforms. These are then used together with a bit accurate MAC/PHY simulator to estimate the frame loss rate, the transmission delay, and the jitter for a steady flow of transmit frames. Time correlated channels are required to correctly simulate the bursty nature of packet loss in a wireless channel. The Doppler spread is shown to have a strong effect on the performance of the ARQ mechanism in the MAC layer. Delay is computed as the sum of the transmission delay and the accumulated queuing delay in the MAC buffer. Delay and frame loss are compared for time correlated and time uncorrelated fading channels. Compared to the slow fading case, in a fast fading channel fewer retransmissions are required and the end-to-end delay is significantly reduced. When channel conditions are poor the simulated delay and frame loss rate are seriously underestimated when time uncorrelated fading is assumed. To analyze the performance of video codecs, we show that a time correlated channel model must be combined with a dedicated 802.11a/g MAC/PHY simulation
Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training
No full textBackground: Particle Swarm Optimization (PSO) is an established method for parameter optimization. It represents a population-based adaptive optimization technique that is influenced by several "strategy parameters". Choosing reasonable parameter values for the PSO is crucial for its convergence behavior, and depends on the optimization task. We present a method for parameter meta-optimization based on PSO and its application to neural network training. The concept of the Optimized Particle Swarm Optimization (OPSO) is to optimize the free parameters of the PSO by having swarms within a swarm. We assessed the performance of the OPSO method on a set of five artificial fitness functions and compared it to the performance of two popular PSO implementations. Results: Our results indicate that PSO performance can be improved if meta-optimized parameter sets are applied. In addition, we could improve optimization speed and quality on the other PSO methods in the majority of our experiments. We applied the OPSO method to neural network training with the aim to build a quantitative model for predicting blood-brain barrier permeation of small organic molecules. On average, training time decreased by a factor of four and two in comparison to the other PSO methods, respectively. By applying the OPSO method, a prediction model showing good correlation with training-, test- and validation data was obtained. Conclusion: Optimizing the free parameters of the PSO method can result in performance gain. The OPSO approach yields parameter combinations improving overall optimization performance. Its conceptual simplicity makes implementing the method a straightforward task
Multimedia transmission over IEEE 802.11g WLANs: practical issues and considerations
No full textMultimedia transmission is widely available over wired networks. With the advent of low-cost WLAN devices, the wireless delivery of multimedia content is highly desirable. However, for media requiring low end-to-end latency, the use of WLAN technology introduces many significant challenges. These challenges are further enhanced if multicast/broadcast transmission is employed to serve a wide range of wireless terminals. This paper provides an understanding of the practical issues associated with WLAN multimedia transmission. A cross-layer measurement programme is performed to identify design issues for low-cost off-the-shelf WLAN multimedia systems. Problems identified include i) broadcast/multicast transmission using the slowest link-speed, ii) common link adaptation mechanisms for all clients, iii) lack of a call admission policy, and iv) irreducible PER even in good channel conditions
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