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To produce a complete 3D reconstruction of a large-scale architectural scene, both ground and aerial images are usually captured. A common approach is to first reconstruct the models from different image sources separately, and al...
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To produce a complete 3D reconstruction of a large-scale architectural scene, both ground and aerial images are usually captured. A common approach is to first reconstruct the models from different image sources separately, and align thetn afterwards. Using this pipeline, this work proposes an accurate and efficient approach for ground-to-aerial model alignment in a coarse-to-fine manner. First, both the ground model and aerial model are transformed into the geo-referenced coordinate system using GPS meta-information for coarse alignment. Then, the coarsely aligned models are refined by a similarity transformation that is estimated based on 3D point correspondences between them, and the 3D point correspondences are determined in a 2D-image-matching manner by considering the rich textural and contextual information in the 2D images. Due to the dramatic differences in viewpoint and scale between ground and aerial images, which make matching them directly nearly impossible, we perform an intermediate view-synthesis step to mitigate the matching difficulty. To this end, the following three key issues are addressed: (a) selecting a suitable subset of aerial images to cover the ground model properly; (b) synthesizing images from the ground model under the viewpoints of the selected aerial images; and finally, (c) obtaining the 2D point matches between the synthesized images and the selected aerial images. The experimental results show that the proposed model alignment approach is quite effective and outperforms several state-of-the-art techniques in terms of both accuracy and efficiency. (C) 2017 Elsevier Ltd. All rights reserved.
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Ancient Chinese architecture 3D digitalization and documentation is a challenging task for the image based modeling community due to its architectural complexity and structural delicacy. Currently, an effective approach to ancient...
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Ancient Chinese architecture 3D digitalization and documentation is a challenging task for the image based modeling community due to its architectural complexity and structural delicacy. Currently, an effective approach to ancient Chinese architecture 3D reconstruction is to merge the two point clouds, separately obtained from ground and aerial images by the SfM technique. There are two understanding issues should be specially addressed: (1) it is difficult to find the point matches between the images from different sources due to their remarkable variations in viewpoint and scale; (2) due to the inevitable drift phenomenon in any SfM reconstruction process, the resulting two point clouds are no longer strictly related by a single similarity transformation as it should be theoretically. To address these two issues, a new point cloud merging method is proposed in this work. Our method has the following characteristics: (1) the images are matched by leveraging sparse mesh based image synthesis; (2) the putative point matches are filtered by geometrical consistency check and geometrical model verification; and (3) the two point clouds are merged via bundle adjustment by linking the ground-to-aerial tracks. Extensive experiments show that our method outperforms many of the state-of-the-art approaches in terms of ground-to-aerial image matching and point cloud merging.
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Increasing the availability of Unmanned Aerial Vehicles (UAV’s) platforms leads to a variety of applications for aerial exploration, surveillance, and transport. Many of these applications rely on the communication between the UA...
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Increasing the availability of Unmanned Aerial Vehicles (UAV’s) platforms leads to a variety of applications for aerial exploration, surveillance, and transport. Many of these applications rely on the communication between the UAV and the ground receiver which is subjected to high mobility that may lead to restrictions on link connectivity and throughput. In order to design high throughput and efficient communication schemes for these scenarios, a deep understanding of the communication channel behavior is required, especially taking into account measurement data from flight experiments. Channel propagation in urban environments involves diffraction effects which modify the Line-of-Sight (LoS) contribution of the total received signal, especially when the receiver is located on the ground. This process leads to scenarios where Multiple-Input Multiple-Output (MIMO) signal processing can take advantage from this situation. In this context, the goal of this paper is to study the diffraction effects of the LoS component through spatial correlation metrics of the signal. To accomplish this, we propose the use of a geometric stochastic technique to model the channel behavior which lies between High Altitude Platforms (HAP) and terrestrial link communications.
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Air-to-Ground (A2G) communication is considered as a significant enabler technology in next-generation networks. To make this a reality, a comprehensive understanding of the A2G channels is vital. This paper presents an Elevation ...
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Air-to-Ground (A2G) communication is considered as a significant enabler technology in next-generation networks. To make this a reality, a comprehensive understanding of the A2G channels is vital. This paper presents an Elevation Angle (EA) based two-ray mean path loss model for the A2G channels. In particular, we present closed-form expressions for the path loss with respect to the elevation angle and compare the results with ray-tracing simulation results. Our results show that mean path loss for the A2G channels can be accurately characterized by the proposed EA based two-ray model. Our study investigates different altitudes of the aerial terminal, different types of terrains, and two polarizations, wherein the proposed EA-based two-ray model matches well with the ray-tracing simulation results. Furthermore, a comparison of the proposed model with the other known path loss models in the literature is conducted. Finally, this work reveals an interesting relationship between the elevation angle and the signal down-fades, that these signal down-fades appear at approximately the same elevation angles regardless of the platform altitude. (C) 2021 Elsevier Inc. All rights reserved.
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Air-to-ground (A2G) communication has been attracted great attention due to the gradual popularization of unmanned aerial vehicle (UAV). In this paper, a 3D geometry-based stochastic model (GBSM) for A2G channels is proposed. Mean...
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Air-to-ground (A2G) communication has been attracted great attention due to the gradual popularization of unmanned aerial vehicle (UAV). In this paper, a 3D geometry-based stochastic model (GBSM) for A2G channels is proposed. Meanwhile, the Gauss-Markov mobile model is adopted to generate dynamic trajectories. According to different scattering environments, we establish a reference model and a statistical simulation model for A2G channels, and derive their respective time correlation functions. In particular. the purpose of establishing the statistical simulation model is to reduce complexity, and we verify the consistency of the two models. Then, we analyze the dynamic motion scenarios generated by Gauss-Markov process, and their effects on A2G channel correlation. Finally, the good conformities of time correlation curves with the existing measurement data and sphere model verify the reliability of our proposed models. (C) 2019 Elsevier GmbH. All rights reserved.
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Interest in high-altitude platforms (HAPs) has been increasing recently, especially with the rapid technical development in solar panels' efficiency, energy storage, antenna design, and lightweight materials for aircraft parts. Th...
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Interest in high-altitude platforms (HAPs) has been increasing recently, especially with the rapid technical development in solar panels' efficiency, energy storage, antenna design, and lightweight materials for aircraft parts. These factors make high-altitude platforms more applicable in a wide variety of military, security, relief, and civilian applications. This paper provides overview on the high-altitude platforms and their advantages compared terrestrial and satellite communications. This paper also surveys the air-to-ground channel model used for HAPs, channel performance metrics, and optimizing various HAPs parameters..
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The capability of associating an image to its geographical location is a significant concern in journalism and digital forensics. Given the availability of geo-tagged satellite imagery for most of the Earth's surface, retrieving t...
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The capability of associating an image to its geographical location is a significant concern in journalism and digital forensics. Given the availability of geo-tagged satellite imagery for most of the Earth's surface, retrieving the location of a generic picture can be addressed as a cross-view image matching between aerial and ground views. In this paper, we outline some initial steps toward the development of a fully-unsupervised algorithm for ground-to-aerial image matching, exploiting the view-invariant adjacency relationships of the landmarks appearing in both views. We introduce a graph-based strategy that, given a set of pre-extracted landmarks, localizes the viewpoint of a ground-level 360-degree image within a broad aerial view of the same area, by matching the respective landmark graphs according to a specifically designed likelihood model.
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In this letter, we study the on-demand unmanned aerial vehicle mounted base stations (UAV-BS) placement problem for arbitrarily distributed users. This UAV-BS placement problem is modeled as a knapsack-like problem, which is NP-co...
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In this letter, we study the on-demand unmanned aerial vehicle mounted base stations (UAV-BS) placement problem for arbitrarily distributed users. This UAV-BS placement problem is modeled as a knapsack-like problem, which is NP-complete. We propose a density-aware placement algorithm to maximize the number of covered users subject to the constraint of the minimum required data rates per user. Simulations are conducted to evaluate the performance of the proposed algorithm in a real environment with different user densities. Our numerical results indicate that for various user densities our proposed solution can service more users with guaranteed data rates compared to the existing method, while reducing the transmit power by 29%.
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This paper studies a cooperative relay network that comprises an unmanned aerial vehicle (UAV) enabling amplify-and-forward (AF) and power splitting (PS) based energy harvesting. The considered system can be constructed in various...
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This paper studies a cooperative relay network that comprises an unmanned aerial vehicle (UAV) enabling amplify-and-forward (AF) and power splitting (PS) based energy harvesting. The considered system can be constructed in various environments such as suburban, urban, dense urban, and high-rise urban where the air-to-ground channels are model by a mixture of Rayleigh and Nakagami-m fading. Then, outage probability and ergodic capacity are provided under different environment-based parameters. Optimal PS ratios are also provided under normal and high transmit power regimes. Finally, the accuracy of the analytical results is validated through Monte Carlo methods.
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This study proposed the development plan of a novel aerial-to-ground remote sensing (AGRS) system for surveying the land scenes of interest. Specifically, the AGRS system is composed by integrating an unmanned aerial vehicle (UAV)...
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This study proposed the development plan of a novel aerial-to-ground remote sensing (AGRS) system for surveying the land scenes of interest. Specifically, the AGRS system is composed by integrating an unmanned aerial vehicle (UAV) imaging system and a mobile mapping system (MMS), onboard whose platform a control station is also added. The UAV-MMS-collaboration can be classified into two modes – loosely and tightly, respectively related to two efficacy levels of the AGRS – fine-scale mapping in general and target investigating in special cases. The latter scenario can be illustrated by the tasks of fast-responses to the time-critical events, e.g., seeking the accessible roads into disaster areas. These all pose challenging issues. To ensure the premise for AGRS development, a field test was carried out in prior to examine the collaborative effect between its two RS-functional modules. Two typical topics were explored, i.e., self-indicated orthorectification of the UAV images and landcover classification based on information fusion. The final positive results have basically validated the feasibility of the development of the AGRS system.
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