scholarly journals INDOOR POSITIONING AND NAVIGATION BASED ON CONTROL SPHERECAL PANORAMIC IMAGES

2016 ◽  
Vol XLI-B6 ◽  
pp. 251-258 ◽  
Author(s):  
Tsung-Che Huang ◽  
Yi-Hsing Tseng
Keyword(s):  
Indoor Positioning ◽  
Image Features ◽  
Bundle Adjustment ◽  
Target Space ◽  
Mobile Mapping ◽  
Technology Roadmap ◽  
Mapping Technology ◽  
Panoramic Images ◽  
Novel Method ◽  
Indoor And Outdoor

Continuous indoor and outdoor positioning and navigation is the goal to achieve in the field of mobile mapping technology. However, accuracy of positioning and navigation will be largely degraded in indoor or occluded areas, due to receiving weak or less GNSS signals. Targeting the need of high accuracy indoor and outdoor positioning and navigation for mobile mapping applications, the objective of this study is to develop a novel method of indoor positioning and navigation with the use of spherical panoramic image (SPI). Two steps are planned in the technology roadmap. First, establishing a control SPI database that contains a good number of well-distributed control SPIs pre-acquired in the target space. A control SPI means an SPI with known exterior orientation parameters, which can be solved with a network bundle adjustment of SPIs. Having a control SPI database, the target space will be ready to provide the service of positioning and navigation. Secondly, the position and orientation of a newly taken SPI can be solved by using overlapped SPIs searched from the control SPI database. The method of matching SPIs and finding conjugate image features will be developed and tested. Two experiments will be planned and conducted in this paper to test the feasibility and validate the test results of the proposed methods. Analysis of appropriate number and distribution of needed control SPIs will also be included in the experiments with respect to different test cases.

scholarly journals INDOOR POSITIONING AND NAVIGATION BASED ON CONTROL SPHERECAL PANORAMIC IMAGES

2016 ◽  
Vol XLI-B6 ◽  
pp. 251-258
Author(s):  
Tsung-Che Huang ◽  
Yi-Hsing Tseng
Keyword(s):  
Indoor Positioning ◽  
Image Features ◽  
Bundle Adjustment ◽  
Target Space ◽  
Mobile Mapping ◽  
Technology Roadmap ◽  
Mapping Technology ◽  
Panoramic Images ◽  
Novel Method ◽  
Indoor And Outdoor

Continuous indoor and outdoor positioning and navigation is the goal to achieve in the field of mobile mapping technology. However, accuracy of positioning and navigation will be largely degraded in indoor or occluded areas, due to receiving weak or less GNSS signals. Targeting the need of high accuracy indoor and outdoor positioning and navigation for mobile mapping applications, the objective of this study is to develop a novel method of indoor positioning and navigation with the use of spherical panoramic image (SPI). Two steps are planned in the technology roadmap. First, establishing a control SPI database that contains a good number of well-distributed control SPIs pre-acquired in the target space. A control SPI means an SPI with known exterior orientation parameters, which can be solved with a network bundle adjustment of SPIs. Having a control SPI database, the target space will be ready to provide the service of positioning and navigation. Secondly, the position and orientation of a newly taken SPI can be solved by using overlapped SPIs searched from the control SPI database. The method of matching SPIs and finding conjugate image features will be developed and tested. Two experiments will be planned and conducted in this paper to test the feasibility and validate the test results of the proposed methods. Analysis of appropriate number and distribution of needed control SPIs will also be included in the experiments with respect to different test cases.

scholarly journals DEVELOPMENT OF VERSATILE MOBILE MAPPING SYSTEM ON A SMALL SCALE

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 271-275
Author(s):  
T. Tachi ◽  
Y. Wang ◽  
R. Abe ◽  
T. Kato ◽  
N. Maebashi ◽  
...  
Keyword(s):  
Small Scale ◽  
Road Maintenance ◽  
Data Utilization ◽  
Mobile Mapping ◽  
The Road ◽  
Map Generation ◽  
Mapping Technology ◽  
Light Vehicle ◽  
The Difference ◽  
Asset Inventory

Abstract. Mobile mapping technology is an effective method to collect geospatial data with high point density and accuracy. It is mainly used for asset inventory and map generation, as well as road maintenance (detecting road cracks and ruts, and measuring flatness). Equipment of former mobile mapping systems (MMS) is large in size and usually installed (hard-mounted) onto dedicated vehicle. Cost-effectiveness and flexibility of MMS have not been regarded as important until Leica Pegasus series, a much smaller system with integrated and configurable components, come out. In this paper, we show you how we realize a versatile MMS with a Pegasus II loaded on a remodelled Japanese light vehicle (small size and less than a cubic capacity of 660 cc). Besides Pegasus II and data-processing PC, we equip this system with a small crane to bring the sensor onto a different platform, an electric cart to survey narrow roads or pedestrian walkway, and a boat attachment so that the sensor can be fixed on a boat. Thus, one Pegasus II can collect data from various platforms. This paper also discusses the precision and accuracy of the Pegasus II working on various platforms. When mounted on a light vehicle, we verified the accuracy of the difference with GCP and evaluated the accuracy of the road maintenance (detecting road cracks and ruts, and measuring flatness). When mounted on an electric cart, we verified the accuracy of the difference with GCP on a pedestrian road and generated road hazard map as a data utilization. When mounted on a boat, we verified the accuracy of the difference with GCP on a dam slope and created slope shading map of landslide area as a data utilization. It turns out that Pegasus II can totally achieve to required surveying-grade.

Detecting Large Simple Rational Hecke Modules for Γ0(N) via Congruences

2018 ◽  
Vol 2020 (19) ◽  
pp. 6149-6168
Author(s):  
Michael Lipnowski ◽  
George J Schaeffer
Keyword(s):  
Modular Forms ◽  
Class Number ◽  
Target Space ◽  
Large Set ◽  
Hecke Eigenvalues ◽  
Artin's Conjecture ◽  
Number Problem ◽  
Novel Method ◽  
Hecke Modules ◽  
Primitive Roots

Abstract We describe a novel method for bounding the dimension $d$ of the largest simple Hecke submodule of $S_{2}(\Gamma _{0}(N);\mathbb{Q})$ from below. Such bounds are of interest because of their relevance to the structure of $J_{0}(N)$, for instance. In contrast with previous results of this kind, our bound does not rely on the equidistribution of Hecke eigenvalues. Instead, it is obtained via a Hecke-compatible congruence between the target space and a space of modular forms whose Hecke eigenvalues are easily controlled. We prove conditional bounds, the strongest of which is $d\gg _{\epsilon } N^{1/2-\epsilon }$ over a large set of primes $N$, contingent on Soundararajan’s heuristics for the class number problem and Artin’s conjecture on primitive roots. For prime levels $N\equiv 7\mod 8,$ our method yields an unconditional bound of $d\geq \log _{2}\log _{2}(\frac{N}{8})$, which is larger than the known bound of $d\gg \sqrt{\log \log N}$ due to Murty–Sinha and Royer. A stronger unconditional bound of $d\gg \log N$ can be obtained in more specialized (but infinitely many) cases. We also propose a number of Maeda-style conjectures based on our data, and we outline a possible congruence-based approach toward the conjectural Hecke simplicity of $S_{k}(\textrm{SL}_{2}(\mathbb{Z});\mathbb{Q})$.

Automatic Registration of Mobile Mapping System Lidar Points and Panoramic-Image Sequences by Relative Orientation Model

2021 ◽  
Vol 87 (12) ◽  
pp. 913-922
Author(s):  
Ningning Zhu ◽  
Bisheng Yang ◽  
Zhen Dong ◽  
Chi Chen ◽  
Xia Huang ◽  
...  
Keyword(s):  
Image Sequence ◽  
Image Sequences ◽  
Relative Orientation ◽  
Panoramic Image ◽  
Feature Points ◽  
Mobile Mapping ◽  
Orientation Model ◽  
Mapping System ◽  
Panoramic Images ◽  
Mobile Mapping System

To register mobile mapping system (MMS) lidar points and panoramic-image sequences, a relative orientation model of panoramic images (PROM) is proposed. The PROM is suitable for cases in which attitude or orientation parameters are unknown in the panoramic-image sequence. First, feature points are extracted and matched from panoramic-image pairs using the SURF algorithm. Second, these matched feature points are used to solve the relative attitude parameters in the PROM. Then, combining the PROM with the absolute position and attitude parameters of the initial panoramic image, the MMS lidar points and panoramic-image sequence are registered. Finally, the registration accuracy of the PROM method is assessed using corresponding points manually selected from the MMSlidar points and panoramic-image sequence. The results show that three types of MMSdata sources are registered accurately based on the proposed registration method. Our method transforms the registration of panoramic images and lidar points into image feature-point matching, which is suitable for diverse road scenes compared with existing methods.

scholarly journals Three-dimensional mobile mapping system and its use in road engineering

2018 ◽  
Vol 196 ◽  
pp. 04082
Author(s):  
Zuzana Florkova ◽  
Lukas Duris ◽  
Michal Veselovsky ◽  
Stefan Sedivý ◽  
Dasa Kovalova
Keyword(s):  
Data Collection ◽  
Field Data ◽  
Three Dimensional ◽  
Research Paper ◽  
Mobile Mapping ◽  
Road Engineering ◽  
Mapping System ◽  
Field Data Collection ◽  
Mapping Technology ◽  
Mobile Mapping System

The paper focuses on the issue of the use of three-dimensional mobile mapping system and the following processing of obtained data. The first part is devoted to the description of the three-dimensional mobile mapping technology using LiDAR, specifically to the mobile three-dimensional scanner - Lynx SG1 from Teledyne OPTECH. It describes into more details the process of works from the field data collection to their so called "postprocessing" as well as a variety of output options and interpretations of results obtained in the measurements. Advantages of the system together with its limits of use are summarized in the conclusion of the research paper.

A novel method for indoor positioning with passive UHF RFID

2011 ◽  
Vol 3 (3) ◽  
pp. 166
Author(s):  
Jussi Nummela ◽  
Matti Nikkari ◽  
Mikael Soini ◽  
Leena Ukkonen ◽  
Lauri Sydanheimo
Keyword(s):  
Indoor Positioning ◽  
Uhf Rfid ◽  
Passive Uhf Rfid ◽  
Novel Method

scholarly journals CAE-COVIDX: automatic covid-19 disease detection based on x-ray images using enhanced deep convolutional and autoencoder

2021 ◽  
Vol 7 (1) ◽  
pp. 49
Author(s):  
Hanafi Hanafi ◽  
Andri Pranolo ◽  
Yingchi Mao
Keyword(s):  
Confusion Matrix ◽  
Virus Detection ◽  
Image Features ◽  
World Health ◽  
X Rays ◽  
X Ray ◽  
First Case ◽  
Long Time ◽  
Novel Method ◽  
Health Organization

Since the first case in 2019, Corona Virus has been spreading all over the world. World Health Organization (WHO) announced that COVID-19 had become an international pandemic. There is an essential section to handle the spreading of the virus by immediate virus detection for patients. Traditional medical detection requires a long time, a specific laboratory, and a high cost. A method for detecting Covid-19 faster compared to common approaches, such as RT-PCR detection, is needed. The method demonstrated that it could produce an X-ray image with higher accuracy and consumed less time. We propose a novel method to extract image features and to classify COVID-19 using deep CNN combined with Autoencoder (AE) dubbed CAE-COVIDX. We evaluated and compared it with the traditional CNN and existing framework VGG16 involving 400 normal images of non-COVID19 and 400 positive COVID-19 diseases. The performance evaluation was conducted using accuracy, confusion matrix, and loss evaluation. Based on experiment results, the CAE-COVIDX framework outperforms previous methods in several testing scenarios. This framework's ability to detect Covid-19 in various nonstandard image X-rays could effectively help medical employers diagnose Covid-19 patients. It is an important factor to decrease the spreading of Covid-19 massively.

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