scholarly journals UNVEILING LARGE-SCALE HISTORICAL CONTENTS WITH V-SLAM AND MARKERLESS MOBILE AR SOLUTIONS

2021 ◽  
Vol XLVI-M-1-2021 ◽  
pp. 761-768
Author(s):  
A. Torresani ◽  
S. Rigon ◽  
E. M. Farella ◽  
F. Menna ◽  
F. Remondino
Keyword(s):  
Augmented Reality ◽  
Large Scale ◽  
Research Work ◽  
Visual Appearance ◽  
Distinctive Features ◽  
Application Range ◽  
Localization And Mapping ◽  
3D Elements ◽  
Satellite Signal ◽  
Mobile Ar

Abstract. Augmented Reality (AR) is already transforming many fields, from medical applications to industry, entertainment and heritage. In its most common form, AR expands reality with virtual 3D elements, providing users with an enhanced and enriched experience of the surroundings. Until now, most of the research work focused on techniques based on markers or on GNSS/INS positioning. These approaches require either the preparation of the scene or a strong satellite signal to work properly. In this paper, we investigate the use of visual-based methods, i.e., methods that exploit distinctive features of the scene estimated with Visual Simultaneous Localization and Mapping (V-SLAM) algorithms, to determine and track the user position and attitude. The detected features, which encode the visual appearance of the scene, can be saved and later used to track the user in successive AR sessions. Existing AR frameworks like Google ARCore, Apple ARKit and Unity AR Foundation recently introduced visual-based localization in their frameworks, but they target mainly small scenarios. We propose a new Mobile Augmented Reality (MAR) methodology that exploits OPEN-V-SLAM to extend the application range of Unity AR Foundation and better handle large-scale environments. The proposed methodology is successfully tested in both controlled and real-case large heritage scenarios. Results are available also in this video: https://youtu.be/Q7VybmiWIuI.

Konsep Augmented Reality Sebagai Pengembangan Pemasaran Pariwisata dalam Menghadapi New Normal Masa Pandemi Covid-19

2020 ◽  
Vol 7 (2) ◽  
Author(s):  
Ellyta Tambunan ◽  
Anwari Masatip
Keyword(s):  
Augmented Reality ◽  
Large Scale ◽  
Considerable Effect ◽  
User Preferences ◽  
Reference Source ◽  
Online Information ◽  
New Normal ◽  
Digital Service ◽  
Use Of Technology ◽  
Mobile Ar

The use of technology today in various sectors of life is very high, this can also seen from the needs and improvements provided by this digital service. Augmented Reality (AR) is one of the organizations that builds and improves online information today. The Covid-19 pandemic had a considerable effect on the use of this technology with the imposition of large-scale physical distancing, this depends on various sectors that exist today, especially the tourism sector. Therefore, it has a big impact on tourism activities / activities, both on a national and international scale (foreign) who will visit tourist spots / destinations. Augmented Reality has various features that support in various fields, one of which is traveling. The scientific and theoretical studies in this study provide a useful reference source for developers of mobile AR applications, tourism managers, and effective marketing strategies in facing the new normal era today. So that tourism businesses or tourist destinations better understand user preferences for mobile AR applications and others that are able to maintain behavior can still enjoy travel with their impulsivity in the context of tourism as a result.  

scholarly journals Potential Of VIRAC* RT-32 And RT-16 Antennas To Serve As Satellite Ground Station

2015 ◽  
Vol 52 (1) ◽  
pp. 68-74
Author(s):  
M. Bleiders ◽  
J. Trokss ◽  
M. Elerts
Keyword(s):  
Large Scale ◽  
Research Work ◽  
Full Time ◽  
Positioning Systems ◽  
Small Satellites ◽  
Ground Station ◽  
Data Rates ◽  
Pointing Accuracy ◽  
Satellite Signal ◽  
Satellite Ground Station

Abstract The basic application of RT-32 and RT-16 parabolic antennas is radio astronomy observations, both the radio-telescopes have been upgraded with state-of-the art cryogenic receivers, and now a large-scale modernization of the infrastructure is underway. Since the radio-astronomical observations are not full-time activities, a research work has been done to clear up whether these antennas, besides the mentioned activities, can be used as a satellite ground station. The main goal of this added functionality is to make possible the use of the extremely high reception systems’ figure-of-merit thus raising the satellite downlink data rates without increasing the on-board power consumption, which would be particularly important for developers of small satellites. In this paper, the progress in the research project is reported, which includes successful S-band satellite signal reception experiments and possible options as to integration of the related equipment into the system so that both functionalities could successfully coexist. Performance of the existing and the upgraded antenna positioning systems is estimated to determine if the latter are usable even for servicing low-Earth orbiting satellites. In addition, possible options are considered as to upgrading the system with automatic beam tracking capability, which would increase the antenna pointing accuracy even further.

scholarly journals Edge-assisted Collaborative Image Recognition for Mobile Augmented Reality

2022 ◽  
Vol 18 (1) ◽  
pp. 1-31
Author(s):  
Guohao Lan ◽  
Zida Liu ◽  
Yunfan Zhang ◽  
Tim Scargill ◽  
Jovan Stojkovic ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Image Recognition ◽  
Large Scale ◽  
Data Augmentation ◽  
Recognition Accuracy ◽  
Image Distortion ◽  
Mobile Augmented Reality ◽  
The Real ◽  
In The Wild ◽  
Mobile Ar

Mobile Augmented Reality (AR), which overlays digital content on the real-world scenes surrounding a user, is bringing immersive interactive experiences where the real and virtual worlds are tightly coupled. To enable seamless and precise AR experiences, an image recognition system that can accurately recognize the object in the camera view with low system latency is required. However, due to the pervasiveness and severity of image distortions, an effective and robust image recognition solution for “in the wild” mobile AR is still elusive. In this article, we present CollabAR, an edge-assisted system that provides distortion-tolerant image recognition for mobile AR with imperceptible system latency . CollabAR incorporates both distortion-tolerant and collaborative image recognition modules in its design. The former enables distortion-adaptive image recognition to improve the robustness against image distortions, while the latter exploits the spatial-temporal correlation among mobile AR users to improve recognition accuracy. Moreover, as it is difficult to collect a large-scale image distortion dataset, we propose a Cycle-Consistent Generative Adversarial Network-based data augmentation method to synthesize realistic image distortion. Our evaluation demonstrates that CollabAR achieves over 85% recognition accuracy for “in the wild” images with severe distortions, while reducing the end-to-end system latency to as low as 18.2 ms.

scholarly journals Visual SLAM Based Spatial Recognition and Visualization Method for Mobile AR Systems

2022 ◽  
Vol 5 (1) ◽  
pp. 11
Author(s):  
Jooeun Song ◽  
Joongjin Kook
Keyword(s):  
Machine Learning ◽  
Augmented Reality ◽  
Research And Development ◽  
Open Source ◽  
Simultaneous Localization And Mapping ◽  
Visualization Method ◽  
Visual Slam ◽  
Localization And Mapping ◽  
Mobile Ar ◽  
Spatial Recognition

The simultaneous localization and mapping (SLAM) market is growing rapidly with advances in Machine Learning, Drones, and Augmented Reality (AR) technologies. However, due to the absence of an open source-based SLAM library for developing AR content, most SLAM researchers are required to conduct their own research and development to customize SLAM. In this paper, we propose an open source-based Mobile Markerless AR System by building our own pipeline based on Visual SLAM. To implement the Mobile AR System of this paper, we use ORB-SLAM3 and Unity Engine and experiment with running our system in a real environment and confirming it in the Unity Engine’s Mobile Viewer. Through this experimentation, we can verify that the Unity Engine and the SLAM System are tightly integrated and communicate smoothly. In addition, we expect to accelerate the growth of SLAM technology through this research.

Green synthesis, characterization of silver sulfide nanoparticles and antibacterial activity evaluation

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Antibacterial Activity ◽  
Large Scale ◽  
Research Work ◽  
Silver Sulfide ◽  
Morphological Properties ◽  
Effective Diameter ◽  
Novel Approach ◽  
Transmission Electron ◽  
Green Route ◽  
Silver Sulfide Nanoparticles

This research work presents a facile and green route for synthesis silver sulfide (Ag2SNPs) nanoparticles from silver nitrate (AgNO3) and sodium sulfide nonahydrate (Na2S.9H2O) in the presence of rosemary leaves aqueous extract at ambient temperature (27 oC). Structural and morphological properties of Ag2SNPs nanoparticles were analyzed by X-ray diffraction (XRD) and transmission electron microscopy (TEM). The surface Plasmon resonance for Ag2SNPs was obtained around 355 nm. Ag2SNPs was spherical in shape with an effective diameter size of 14 nm. Our novel approach represents a promising and effective method to large scale synthesis of eco-friendly antibacterial activity silver sulfide nanoparticles.

Bottlenecks in the Implementation of On-Site Wastewater Treatment Plants on a Large Scale in The Netherlands

1990 ◽  
Vol 22 (3-4) ◽  
pp. 291-298
Author(s):  
Frits A. Fastenau ◽  
Jaap H. J. M. van der Graaf ◽  
Gerard Martijnse
Keyword(s):  
Wastewater Treatment ◽  
The Netherlands ◽  
Large Scale ◽  
Wastewater Treatment Plants ◽  
Housing Stock ◽  
Research Work ◽  
Field Research ◽  
Domestic Wastewater ◽  
Research Programme ◽  
Definition Of

More than 95 % of the total housing stock in the Netherlands is connected to central sewerage systems and in most cases the wastewater is treated biologically. As connection to central sewerage systems has reached its economic limits, interest in on-site treatment of the domestic wastewater of the remaining premises is increasing. A large scale research programme into on-site wastewater treatment up to population equivalents of 200 persons has therefore been initiated by the Dutch Ministry of Housing, Physical Planning and Environment. Intensive field-research work did establish that the technological features of most on-site biological treatment systems were satisfactory. A large scale implementation of these systems is however obstructed in different extents by problems of an organisational, financial and/or juridical nature and management difficulties. At present research is carried out to identify these bottlenecks and to analyse possible solutions. Some preliminary results are given which involve the following ‘bottlenecks':-legislation: absence of co-ordination and absence of a definition of ‘surface water';-absence of subsidies;-ownership: divisions in task-setting of Municipalities and Waterboards; divisions involved with cost-sharing;-inspection; operational control and maintenance; organisation of management;-discharge permits;-pollution levy;-sludge disposal. Final decisions and practical elaboration of policies towards on-site treatment will have to be formulated in a broad discussion with all the authorities and interest groups involved.

DeepSSPred: A Deep Learning Based Sulfenylation site predictor via a novel n-segmented optimize federated feature encoder

2020 ◽  
Vol 27 ◽  
Author(s):  
Zaheer Ullah Khan ◽  
Dechang Pi
Keyword(s):  
Large Scale ◽  
Computational Models ◽  
Research Work ◽  
Training Data ◽  
Training Dataset ◽  
Validation Dataset ◽  
Cytokine Signaling ◽  
Minority Class ◽  
Independent Dataset ◽  
Feature Encoding

Background: S-sulfenylation (S-sulphenylation, or sulfenic acid) proteins, are special kinds of post-translation modification, which plays an important role in various physiological and pathological processes such as cytokine signaling, transcriptional regulation, and apoptosis. Despite these aforementioned significances, and by complementing existing wet methods, several computational models have been developed for sulfenylation cysteine sites prediction. However, the performance of these models was not satisfactory due to inefficient feature schemes, severe imbalance issues, and lack of an intelligent learning engine. Objective: In this study, our motivation is to establish a strong and novel computational predictor for discrimination of sulfenylation and non-sulfenylation sites. Methods: In this study, we report an innovative bioinformatics feature encoding tool, named DeepSSPred, in which, resulting encoded features is obtained via n-segmented hybrid feature, and then the resampling technique called synthetic minority oversampling was employed to cope with the severe imbalance issue between SC-sites (minority class) and non-SC sites (majority class). State of the art 2DConvolutional Neural Network was employed over rigorous 10-fold jackknife cross-validation technique for model validation and authentication. Results: Following the proposed framework, with a strong discrete presentation of feature space, machine learning engine, and unbiased presentation of the underline training data yielded into an excellent model that outperforms with all existing established studies. The proposed approach is 6% higher in terms of MCC from the first best. On an independent dataset, the existing first best study failed to provide sufficient details. The model obtained an increase of 7.5% in accuracy, 1.22% in Sn, 12.91% in Sp and 13.12% in MCC on the training data and12.13% of ACC, 27.25% in Sn, 2.25% in Sp, and 30.37% in MCC on an independent dataset in comparison with 2nd best method. These empirical analyses show the superlative performance of the proposed model over both training and Independent dataset in comparison with existing literature studies. Conclusion : In this research, we have developed a novel sequence-based automated predictor for SC-sites, called DeepSSPred. The empirical simulations outcomes with a training dataset and independent validation dataset have revealed the efficacy of the proposed theoretical model. The good performance of DeepSSPred is due to several reasons, such as novel discriminative feature encoding schemes, SMOTE technique, and careful construction of the prediction model through the tuned 2D-CNN classifier. We believe that our research work will provide a potential insight into a further prediction of S-sulfenylation characteristics and functionalities. Thus, we hope that our developed predictor will significantly helpful for large scale discrimination of unknown SC-sites in particular and designing new pharmaceutical drugs in general.

scholarly journals Spatial multiplexing holographic combiner for glasses-free augmented reality

Nanophotonics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 3003-3010
Author(s):  
Jiacheng Shi ◽  
Wen Qiao ◽  
Jianyu Hua ◽  
Ruibin Li ◽  
Linsen Chen
Keyword(s):  
Augmented Reality ◽  
Large Scale ◽  
Motion Parallax ◽  
Visible Spectrum ◽  
Physical World ◽  
Spatial Multiplexing ◽  
White Balance ◽  
Full Color ◽  
Entire Visible Spectrum ◽  
3D Scene

AbstractGlasses-free augmented reality is of great interest by fusing virtual 3D images naturally with physical world without the aid of any wearable equipment. Here we propose a large-scale spatial multiplexing holographic see-through combiner for full-color 3D display. The pixelated metagratings with varied orientation and spatial frequency discretely reconstruct the propagating lightfield. The irradiance pattern of each view is tailored to form super Gaussian distribution with minimized crosstalk. What’s more, spatial multiplexing holographic combiner with customized aperture size is adopted for the white balance of virtually displayed full-color 3D scene. In a 32-inch prototype, 16 views form a smooth parallax with a viewing angle of 47°. A high transmission (>75%) over the entire visible spectrum range is achieved. We demonstrated that the displayed virtual 3D scene not only preserved natural motion parallax, but also mixed well with the natural objects. The potential applications of this study include education, communication, product design, advertisement, and head-up display.

scholarly journals Cultural Diplomacy and Europe's Twenty Years’ Crisis, 1919–1939: Introduction

2021 ◽  
pp. 1-15
Author(s):  
Benjamin G. Martin ◽  
Elisabeth Piller
Keyword(s):  
Large Scale ◽  
Cultural Diplomacy ◽  
Good Reason ◽  
Political Leaders ◽  
Distinctive Features ◽  
The Arts ◽  
International Exposition ◽  
German Nation ◽  
Iconic Image ◽  
Industrial Designers

Photographs of the German and Soviet pavilions facing off at the Paris International Exposition in 1937 offer an iconic image of the interwar period, and with good reason. This image captures the interwar period's great conflict of ideologies, the international interconnectedness of the age and the aestheticisation of political and ideological conflict in the age of mass media and mass spectacle. [Figure 1] Last but not least, it captures the importance in the 1930s of what we now call cultural diplomacy. Both pavilions – Germany's, in Albert Speer's neo-classical tower bloc crowned with a giant swastika, and the Soviet Union's, housed in Boris Iofan's forward-thrusting structure topped by Vera Mukhina's monumental sculptural group – represented the outcome of a large-scale collaboration between political leaders and architects, artists, intellectuals and graphic and industrial designers seeking to present their country to foreign visitors in a manner designed to advance the country's interests in the international arena. Each pavilion, that is, made an outreach that was diplomatic – in the sense that it sought to mediate between distinct polities – using means that were cultural – in the sense that they deployed refined aesthetic practices (like the arts and architecture) and in the sense that they highlighted the distinctive features, or ‘culture’, of a particular group (like the German nation or the Soviet state).

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