scholarly journals TWO-STEP CAMERA CALIBRATION METHOD DEVELOPED FOR MICRO UAV'S

2016 ◽  
Vol XLI-B1 ◽  
pp. 829-833 ◽  
Author(s):  
M. Gašparović ◽  
D. Gajski
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Calibration Procedure ◽  
Unmanned Aircraft ◽  
Sensor Calibration ◽  
Step Process ◽  
Complex Process ◽  
One Step ◽  
Accurate Procedure ◽  
Wide Angle Camera

The development of unmanned aerial vehicles (UAVs) and continuous price reduction of unmanned systems attracted us to this research. Professional measuring systems are dozens of times more expensive and often heavier than "amateur", non-metric UAVs. For this reason, we tested the DJI Phantom 2 Vision Plus UAV. Phantom’s smaller mass and velocity can develop less kinetic energy in relation to the professional measurement platforms, which makes it potentially less dangerous for use in populated areas. In this research, we wanted to investigate the ability of such non-metric UAV and find the procedures under which this kind of UAV may be used for the photogrammetric survey. It is important to emphasize that UAV is equipped with an ultra wide-angle camera with 14MP sensor. Calibration of such cameras is a complex process. In the research, a new two-step process is presented and developed, and the results are compared with standard one-step camera calibration procedure. Two-step process involves initially removed distortion on all images, and then uses these images in the phototriangulation with self-calibration. The paper presents statistical indicators which proved that the proposed two-step process is better and more accurate procedure for calibrating those types of cameras than standard one-step calibration. Also, we suggest two-step calibration process as the standard for ultra-wideangle cameras for unmanned aircraft.

scholarly journals TWO-STEP CAMERA CALIBRATION METHOD DEVELOPED FOR MICRO UAV'S

2016 ◽  
Vol XLI-B1 ◽  
pp. 829-833 ◽  
Author(s):  
M. Gašparović ◽  
D. Gajski
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Calibration Procedure ◽  
Unmanned Aircraft ◽  
Sensor Calibration ◽  
Step Process ◽  
Complex Process ◽  
One Step ◽  
Accurate Procedure ◽  
Wide Angle Camera

The development of unmanned aerial vehicles (UAVs) and continuous price reduction of unmanned systems attracted us to this research. Professional measuring systems are dozens of times more expensive and often heavier than "amateur", non-metric UAVs. For this reason, we tested the DJI Phantom 2 Vision Plus UAV. Phantom’s smaller mass and velocity can develop less kinetic energy in relation to the professional measurement platforms, which makes it potentially less dangerous for use in populated areas. In this research, we wanted to investigate the ability of such non-metric UAV and find the procedures under which this kind of UAV may be used for the photogrammetric survey. It is important to emphasize that UAV is equipped with an ultra wide-angle camera with 14MP sensor. Calibration of such cameras is a complex process. In the research, a new two-step process is presented and developed, and the results are compared with standard one-step camera calibration procedure. Two-step process involves initially removed distortion on all images, and then uses these images in the phototriangulation with self-calibration. The paper presents statistical indicators which proved that the proposed two-step process is better and more accurate procedure for calibrating those types of cameras than standard one-step calibration. Also, we suggest two-step calibration process as the standard for ultra-wideangle cameras for unmanned aircraft.

scholarly journals An Innovative Calibration Method for the Inversion of Satellite Observations

2010 ◽  
Vol 49 (12) ◽  
pp. 2458-2473 ◽  
Author(s):  
Filipe Aires ◽  
Frédéric Bernardo ◽  
Héléne Brogniez ◽  
Catherine Prigent
Keyword(s):  
Water Vapor ◽  
Single Channel ◽  
Weather Prediction ◽  
Calibration Method ◽  
Calibration Procedure ◽  
Satellite Observations ◽  
Radiative Transfer Model ◽  
Sensor Calibration ◽  
Transfer Model ◽  
Nwp Model

Abstract Retrieval schemes often use two important components: 1) a radiative transfer model (RTM) inside the retrieval procedure or to construct the learning dataset for the training of the statistical retrieval algorithms and 2) a numerical weather prediction (NWP) model to provide a first guess or, again, to construct a learning dataset. This is particularly true in operational centers. As a consequence, any physical retrieval or similar method is limited by inaccuracies in the RTM and NWP models on which it is based. In this paper, a method for partially compensating for these errors as part of the sensor calibration is presented and evaluated. In general, RTM/NWP errors are minimized as best as possible prior to the training of the retrieval method, and then tolerated. The proposed method reduces these unknown and generally nonlinear residual errors by training a separate preprocessing neural network (NN) to produce calibrated radiances from real satellite data that approximate those radiances produced by the “flawed” NWP and RTM models. The final “compensated/flawed” retrieval assures better internal consistency of the retrieval procedure and then produces more accurate results. To the authors’ knowledge, this type of NN model has not been used yet for this purpose. The calibration approach is illustrated here on one particular application: the retrieval of atmospheric water vapor from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and the Humidity Sounder for Brazil (HSB) measurements for nonprecipitating scenes, over land and ocean. Before being inverted, the real observations are “projected” into the space of the RTM simulation space from which the retrieval is designed. Validation of results is performed with radiosonde measurements and NWP analysis departures. This study shows that the NN calibration of the AMSR-E/HSB observations improves water vapor inversion, over ocean and land, for both clear and cloudy situations. The NN calibration is efficient and very general, being applicable to a large variety of problems. The nonlinearity of the NN allows for the calibration procedure to be state dependent and adaptable to specific cases (e.g., the same correction will not be applied to medium-range measurement and to extreme conditions). Its multivariate nature allows for a full exploitation of the complex correlation structure among the instrument channels, making the calibration of each single channel more robust. The procedure would make it possible to project the satellite observations in a reference observational space defined by radiosonde measurements, RTM simulations, or other instrument observational space.

scholarly journals CALIBRATION PROCEDURES ON OBLIQUE CAMERA SETUPS

2016 ◽  
Vol XLI-B1 ◽  
pp. 205-209 ◽  
Author(s):  
G. Kemper ◽  
B. Melykuti ◽  
C. Yu
Keyword(s):  
Camera Calibration ◽  
Homeland Security ◽  
City Planning ◽  
Data Extraction ◽  
Iteration Process ◽  
Calibration Procedure ◽  
Single Camera ◽  
Urban Dynamics ◽  
3D City Model ◽  
One Step

Beside the creation of virtual animated 3D City models, analysis for homeland security and city planning, the accurately determination of geometric features out of oblique imagery is an important task today. Due to the huge number of single images the reduction of control points force to make use of direct referencing devices. This causes a precise camera-calibration and additional adjustment procedures. <br><br> This paper aims to show the workflow of the various calibration steps and will present examples of the calibration flight with the final 3D City model. In difference to most other software, the oblique cameras are used not as co-registered sensors in relation to the nadir one, all camera images enter the AT process as single pre-oriented data. This enables a better post calibration in order to detect variations in the single camera calibration and other mechanical effects. <br><br> The shown sensor (Oblique Imager) is based o 5 Phase One cameras were the nadir one has 80 MPIX equipped with a 50 mm lens while the oblique ones capture images with 50 MPix using 80 mm lenses. The cameras are mounted robust inside a housing to protect this against physical and thermal deformations. The sensor head hosts also an IMU which is connected to a POS AV GNSS Receiver. The sensor is stabilized by a gyro-mount which creates floating Antenna –IMU lever arms. They had to be registered together with the Raw GNSS-IMU Data. <br><br> The camera calibration procedure was performed based on a special calibration flight with 351 shoots of all 5 cameras and registered the GPS/IMU data. This specific mission was designed in two different altitudes with additional cross lines on each flying heights. The five images from each exposure positions have no overlaps but in the block there are many overlaps resulting in up to 200 measurements per points. On each photo there were in average 110 well distributed measured points which is a satisfying number for the camera calibration. In a first step with the help of the nadir camera and the GPS/IMU data, an initial orientation correction and radial correction were calculated. With this approach, the whole project was calculated and calibrated in one step. During the iteration process the radial and tangential parameters were switched on individually for the camera heads and after that the camera constants and principal point positions were checked and finally calibrated. <br><br> Besides that, the bore side calibration can be performed either on basis of the nadir camera and their offsets, or independently for each camera without correlation to the others. This must be performed in a complete mission anyway to get stability between the single camera heads. Determining the lever arms of the nodal-points to the IMU centre needs more caution than for a single camera especially due to the strong tilt angle. <br><br> Prepared all these previous steps, you get a highly accurate sensor that enables a fully automated data extraction with a rapid update of you existing data. Frequently monitoring urban dynamics is then possible in fully 3D environment.

Development of a Non-Invasive Calibration Method for Ocular Tactile Tonometry

2013 ◽  
Author(s):  
Eniko T. Enikov ◽  
Péter P. Polyvás
Keyword(s):  
Calibration Method ◽  
Calibration Procedure ◽  
Superior Performance ◽  
Sensor Calibration ◽  
Ann Model ◽  
Element Analysis ◽  
Reduced Order ◽  
Non Invasive ◽  
Calibration Methods ◽  
Artificial Neural Network Ann

This article describes a novel method of indirect estimation of intra-ocular pressure using tactile sensors. Two sensor calibration methods have been demonstrated: an artificial neural network (ANN) model and a phenomenological reduced-parameter model based on finite element analysis. The ANN method showed superior performance with an accuracy of +/− 0.7 mmHg, while the reduced order method showed an accuracy of +/− 3.11 mmHg. The latter method however allows calibration of the tactile tonometer from a single pressure measurement if the geometry of the probes is known and satisfying certain solvability conditions. The ANN method was demonstrated using experiment data, while the reduced-order model was tested numerically. Due to its indirect and non-invasive nature, the proposed tactile measurement method can be used in the development of a self-administered home tonometer for management of glaucoma, however the presence of an eye lid might require modification of the calibration procedure outlined here.

scholarly journals CALIBRATION PROCEDURES ON OBLIQUE CAMERA SETUPS

2016 ◽  
Vol XLI-B1 ◽  
pp. 205-209
Author(s):  
G. Kemper ◽  
B. Melykuti ◽  
C. Yu
Keyword(s):  
Camera Calibration ◽  
Homeland Security ◽  
City Planning ◽  
Data Extraction ◽  
Iteration Process ◽  
Calibration Procedure ◽  
Single Camera ◽  
Urban Dynamics ◽  
3D City Model ◽  
One Step

Beside the creation of virtual animated 3D City models, analysis for homeland security and city planning, the accurately determination of geometric features out of oblique imagery is an important task today. Due to the huge number of single images the reduction of control points force to make use of direct referencing devices. This causes a precise camera-calibration and additional adjustment procedures. <br><br> This paper aims to show the workflow of the various calibration steps and will present examples of the calibration flight with the final 3D City model. In difference to most other software, the oblique cameras are used not as co-registered sensors in relation to the nadir one, all camera images enter the AT process as single pre-oriented data. This enables a better post calibration in order to detect variations in the single camera calibration and other mechanical effects. <br><br> The shown sensor (Oblique Imager) is based o 5 Phase One cameras were the nadir one has 80 MPIX equipped with a 50 mm lens while the oblique ones capture images with 50 MPix using 80 mm lenses. The cameras are mounted robust inside a housing to protect this against physical and thermal deformations. The sensor head hosts also an IMU which is connected to a POS AV GNSS Receiver. The sensor is stabilized by a gyro-mount which creates floating Antenna –IMU lever arms. They had to be registered together with the Raw GNSS-IMU Data. <br><br> The camera calibration procedure was performed based on a special calibration flight with 351 shoots of all 5 cameras and registered the GPS/IMU data. This specific mission was designed in two different altitudes with additional cross lines on each flying heights. The five images from each exposure positions have no overlaps but in the block there are many overlaps resulting in up to 200 measurements per points. On each photo there were in average 110 well distributed measured points which is a satisfying number for the camera calibration. In a first step with the help of the nadir camera and the GPS/IMU data, an initial orientation correction and radial correction were calculated. With this approach, the whole project was calculated and calibrated in one step. During the iteration process the radial and tangential parameters were switched on individually for the camera heads and after that the camera constants and principal point positions were checked and finally calibrated. <br><br> Besides that, the bore side calibration can be performed either on basis of the nadir camera and their offsets, or independently for each camera without correlation to the others. This must be performed in a complete mission anyway to get stability between the single camera heads. Determining the lever arms of the nodal-points to the IMU centre needs more caution than for a single camera especially due to the strong tilt angle. <br><br> Prepared all these previous steps, you get a highly accurate sensor that enables a fully automated data extraction with a rapid update of you existing data. Frequently monitoring urban dynamics is then possible in fully 3D environment.

Functionalized aluminum-catalyzed silicon nanowire formation and radial junction photovoltaic devices

Nanoscale ◽  
2021 ◽  
Author(s):  
Wipakorn Jevasuwan ◽  
Naoki Fukata
Keyword(s):  
Surface Modification ◽  
Solar Cells ◽  
Surface Defects ◽  
Silicon Nanowire ◽  
Photovoltaic Devices ◽  
Step Process ◽  
One Step ◽  
Length Reduction

Vertical Al-catalyzed SiNW arrays with shaped surfaces were synthesized by a one-step process and NW-based solar cells were demonstrated with optimized NW surface defects through surface modification and length reduction.

Camera Calibration Method Based on Circle Plane Board

2013 ◽  
Vol 475-476 ◽  
pp. 184-187
Author(s):  
Wen Guo Li ◽  
Shao Jun Duan
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Lens Distortion ◽  
Edge Extraction ◽  
Circle Plane ◽  
Circle Centre ◽  
Extraction Algorithm ◽  
Calibration Algorithm ◽  
Characteristic Points ◽  
Distortion Parameters

We present a camera calibration method based on circle plane board. The centres of circles on plane are regarded as the characteristic points, which are used to implement camera calibration. The proposed calibration is more accurate than many previous calibration algorithm because of the merit of the coordinate of circle centre being obtained from thousand of of edge pionts of ellipse, which is very reliable to image noise caused by edge extraction algorithm. Experiments shows the proposed algorithm can obtain high precise inner parameters, and lens distortion parameters.

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