scholarly journals ADAPTIVE WEIGHTING OF IMAGE OBSERVATIONS FOR SELF-CALIBRATION WITH FISHEYE IMAGES

2021 ◽  
Vol V-1-2021 ◽  
pp. 81-87
Author(s):  
L. F. Castanheiro ◽  
A. M. G. Tommaselli ◽  
M. B. Campos ◽  
A. Berveglieri
Keyword(s):  
Standard Deviation ◽  
Radial Distance ◽  
Relative Orientation ◽  
Bundle Adjustment ◽  
Experimental Results ◽  
Unit Weight ◽  
Projection Model ◽  
Distortion Model ◽  
Adaptive Weighting ◽  
Orientation Parameters

Abstract. Fisheye cameras have been widely used in photogrammetric applications, but conventional techniques must be adapted to consider specific features of fisheye images, such as nonuniform resolution in the images. This work presents experimental results of an adaptive weighting of the observation in a self-calibrating bundle adjustment to cope with the nonuniform resolution of fisheye images. GoPro Fusion and Ricoh Theta dual-fisheye systems were calibrated with bundle adjustment based on equisolid-angle projection model combined with Conrady-Brown distortion model. The image observations were weighted as a function of radial distance based on combining loss of resolution and blurring in fisheye images. The results were compared with a similar trial by considering the same standard deviation for all image observations. The use of adaptive weighting of image observations reduced the estimated standard deviation of unit weight by 30 % and 50 % with GoPro Fusion and Ricoh Theta images, respectively. The estimation of relative orientation parameters (ROPs) was also improved (∼50 %) when using adaptive weighting for image observations.

scholarly journals Linear Approach for Initial Recovery of the Exterior Orientation Parameters of Randomly Captured Images by Low-Cost Mobile Mapping Systems

2014 ◽  
Vol XL-1 ◽  
pp. 149-154 ◽  
Author(s):  
F. He ◽  
A. Habib
Keyword(s):  
Relative Orientation ◽  
Bundle Adjustment ◽  
Adjustment Process ◽  
Coordinate Frame ◽  
Exterior Orientation ◽  
Linear Solution ◽  
Linear Approach ◽  
Initial Recovery ◽  
Orientation Parameters ◽  
Local Coordinate Frame

In this paper, we present a novel linear approach for the initial recovery of the exterior orientation parameters (EOPs) of images. Similar to the conventional Structure from Motion (SfM) algorithm, the proposed approach is based on a two-step strategy. In the first step, the relative orientation of all possible image stereo-pairs is estimated. In the second step, a local coordinate frame is established, and an incremental image augmentation process is implemented to reference all the remaining images into a local coordinate frame. Since our approach is based on a linear solution for both the relative orientation estimation as well as the initial recovery of the image EOPs, it does not require any initial approximation for the optimization process. Another advantage of our approach is that it does not require any prior knowledge regarding the sequence of the image collection procedure, therefore, it can handle a set of randomly collected images in the absence of GNSS/INS information. In order to illustrate the feasibility of our approach, several experimental tests are conducted on real datasets captured in either a block or linear trajectory configuration. The results demonstrate that the initial image EOPs obtained are accurate and can serve as a good initialization for an additional bundle adjustment process.

scholarly journals Practical In Situ Implementation of a Multicamera Multisystem Calibration

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Ivan Detchev ◽  
Ayman Habib ◽  
Mehdi Mazaheri ◽  
Derek Lichti
Keyword(s):  
Low Cost ◽  
Relative Orientation ◽  
Bundle Adjustment ◽  
Simultaneous Estimation ◽  
Multiple Systems ◽  
System Calibration ◽  
Different Types ◽  
Optimal Accuracy ◽  
Orientation Parameters

Consumer-grade cameras are generally low-cost and available off-the-shelf, so having multicamera photogrammetric systems for 3D reconstruction is both financially feasible and practical. Such systems can be deployed in many different types of applications: infrastructure health monitoring, cultural heritage documentation, bio-medicine, as-built surveys, and indoor or outdoor mobile mapping for example. A geometric system calibration is usually necessary before a data acquisition mission in order for the results to have optimal accuracy. A typical system calibration must address the estimation of both the interior and the exterior, or relative, orientation parameters for each camera in the system. This article reviews different ways of performing a calibration of a photogrammetric system consisting of multiple cameras. It then proposes a methodology for the simultaneous estimation of both the interior and the relative orientation parameters which can work in several different types of scenarios including a multicamera multisystem calibration. A rigorous in situ system calibration was successfully implemented and tested. The same algorithm is able to handle the equivalent to a traditional-style bundle adjustment, that is, a network solution without constraints, for a single or multicamera calibrations, and the proposed bundle adjustment with built-in relative orientation constraints for the calibration of a system or multiple systems of cameras.

scholarly journals ON SCALE DEFINITION WITHIN CALIBRATION OF MULTI-CAMERA SYSTEMS IN MULTIMEDIA PHOTOGRAMMETRY

2019 ◽  
Vol XLII-2/W10 ◽  
pp. 93-100 ◽  
Author(s):  
O. Kahmen ◽  
R. Rofallski ◽  
N. Conen ◽  
T. Luhmann
Keyword(s):  
Relative Orientation ◽  
Bundle Adjustment ◽  
Object Space ◽  
Implicit Form ◽  
Camera Systems ◽  
Systematic Effects ◽  
Synthetic Datasets ◽  
Orientation Parameters ◽  
Standard Software ◽  
Implicit Modelling

<p><strong>Abstract.</strong> In multimedia photogrammetry, multi-camera systems often provide scale by a calibrated relative orientation. Camera calibration via bundle adjustment is a well-established standard procedure in single-medium photogrammetry. When using standard software and applying the collinearity equations in multimedia photogrammetry, the refractive interfaces are modelled in an implicit form. This contribution analyses different calibration strategies for bundle-invariant interfaces. To evaluate the effects of implicitly modelling the refractive effects within a bundle adjustment, synthetic datasets are simulated. Contrary to many publications, systematic effects of the exterior orientations can be verified with simulated data. The behaviour of interior, exterior and relative orientation parameters is analysed using error-free synthetic datasets. The relative orientation of a stereo camera shows systematic effects, when the angle of convergence varies and when the synthetic interface is set up at different distances to the camera. It becomes clear, that in most cases the implicit modelling is not suitable for multimedia photogrammetry. An explicit modelling of the refractive interfaces is implemented into a bundle adjustment. This strict model is analysed and compared with the implicit form regarding systematic effects in orientation parameters as well as errors in object space. In a real experiment, the discrepancies between the implicit form using standard software and the explicit modelling using our own implementation are quantified. It is highly advisable to model the interfaces strictly, since the implicit modelling might lead to relevant errors in object space.</p>

scholarly journals ROBUST AND ACCURATE IMAGE-BASED GEOREFERENCING EXPLOITING RELATIVE ORIENTATION CONSTRAINTS

2018 ◽  
Vol IV-2 ◽  
pp. 57-64
Author(s):  
S. Cavegn ◽  
S. Blaser ◽  
S. Nebiker ◽  
N. Haala
Keyword(s):  
Test Site ◽  
Urban Environments ◽  
Relative Orientation ◽  
Bundle Adjustment ◽  
Test Field ◽  
Mobile Mapping ◽  
Mapping System ◽  
Mobile Mapping System ◽  
Accuracy Increase ◽  
Orientation Parameters

Urban environments with extended areas of poor GNSS coverage as well as indoor spaces that often rely on real-time SLAM algorithms for camera pose estimation require sophisticated georeferencing in order to fulfill our high requirements of a few centimeters for absolute 3D point measurement accuracies. Since we focus on image-based mobile mapping, we extended the structure-from-motion pipeline COLMAP with georeferencing capabilities by integrating exterior orientation parameters from direct sensor orientation or SLAM as well as ground control points into bundle adjustment. Furthermore, we exploit constraints for relative orientation parameters among all cameras in bundle adjustment, which leads to a significant robustness and accuracy increase especially by incorporating highly redundant multi-view image sequences. We evaluated our integrated georeferencing approach on two data sets, one captured outdoors by a vehicle-based multi-stereo mobile mapping system and the other captured indoors by a portable panoramic mobile mapping system. We obtained mean RMSE values for check point residuals between image-based georeferencing and tachymetry of 2&amp;thinsp;cm in an indoor area, and 3&amp;thinsp;cm in an urban environment where the measurement distances are a multiple compared to indoors. Moreover, in comparison to a solely image-based procedure, our integrated georeferencing approach showed a consistent accuracy increase by a factor of 2&amp;ndash;3 at our outdoor test site. Due to pre-calibrated relative orientation parameters, images of all camera heads were oriented correctly in our challenging indoor environment. By performing self-calibration of relative orientation parameters among respective cameras of our vehicle-based mobile mapping system, remaining inaccuracies from suboptimal test field calibration were successfully compensated.

scholarly journals NETWORK ADJUSTMENT OF AUTOMATED RELATIVE ORIENTATION FOR A DUAL-CAMERA SYSTEM

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 49-54
Author(s):  
K. Y. Lin ◽  
Y. H. Tseng ◽  
K. W. Chiang
Keyword(s):  
Primary Objective ◽  
Relative Orientation ◽  
Bundle Adjustment ◽  
Stereo Image ◽  
Network Adjustment ◽  
Camera System ◽  
Image Pairs ◽  
Geometric Relationship ◽  
Relationship Of ◽  
Orientation Parameters

Abstract. Visual odometry (VO) is a technique applied to track the dynamic positioning and orientation of a moving platform with one or more cameras taking image sequences. The determination relies on the estimation of relative orientation parameters (ROPs) of time adjacent images. The idea of stereo VO to develop a dual-camera system is adopted in this study. By taking advantage of the calibrated stereo camera, this system is able to recover the true scale of relative translation without the need from additional sensors. However, the scale might not be very accurate, and the error also could exist in the orientation including rotation and translation due to environmental factors such as the illumination and texture. Therefore, the primary objective of this study is to find the optimized theory and method of stereo VO. Through the analysis of the geometric relationship of the time adjacent stereo image pairs, locally optimized network adjustment is developed to improve the accuracy of ROPs.The proposed network adjustment model is verified by the simulation data and experiment data both. ROPs are adopted as observations that would update the states of the image sequence further. Besides, exterior orientation parameters (EOPs) of the dual-camera system could be optimized obviously during the whole operation. In this study, it is worth mentioning that 3D coordinates of object points matched in each image pair are not necessary to be calculated. The conventional bundle adjustment is not adopted, but more accurate EOPs still have been generated automatically during the process.

scholarly journals A Digital Improvement—Trimming a Digital Temperature Sensor with EEPROM Reprogrammable Fuses

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1700
Author(s):  
Anca Mihaela Vasile (Dragan) ◽  
Alina Negut ◽  
Adrian Tache ◽  
Gheorghe Brezeanu
Keyword(s):  
Standard Deviation ◽  
Power Supply ◽  
Temperature Sensor ◽  
Experimental Results ◽  
Temperature Error ◽  
Thermal Sensor ◽  
Memory Cells ◽  
Temperature Range ◽  
Read Only Memory ◽  
Digital Temperature Sensor

An EEPROM (electrically erasable programmable read-only memory) reprogrammable fuse for trimming a digital temperature sensor is designed in a 0.18-µm CMOS EEPROM. The fuse uses EEPROM memory cells, which allow multiple programming cycles by modifying the stored data on the digital trim codes applied to the thermal sensor. By reprogramming the fuse, the temperature sensor can be adjusted with an increased trim variation in order to achieve higher accuracy. Experimental results for the trimmed digital sensor showed a +1.5/−1.0 ℃ inaccuracy in the temperature range of −20 to 125 ℃ for 25 trimmed DTS samples at 1.8 V by one-point calibration. Furthermore, an average mean of 0.40 ℃ and a standard deviation of 0.70 ℃ temperature error were obtained in the same temperature range for power supply voltages from 1.7 to 1.9 V. Thus, the digital sensor exhibits similar performances for the entire power supply range of 1.7 to 3.6 V.

scholarly journals An image dehazing algorithm based on double priors constraint

2018 ◽  
Vol 189 ◽  
pp. 04009
Author(s):  
Kun Liu ◽  
Shiping Wang ◽  
Linyuan He ◽  
Duyan Bi ◽  
Shan Gao
Keyword(s):  
Standard Deviation ◽  
Mean Value ◽  
Experimental Results ◽  
Dark Channel Prior ◽  
Image Dehazing ◽  
Color Distortion ◽  
Local Media ◽  
Dark Channel

Aiming at the color distortion of the restored image in the sky region, we propose an image dehazing algorithm based on double priors constraint. Firstly, we divided the haze image into sky and non-sky regions. Then the Color-lines prior and dark channel prior are used for estimating the transmission of sky and non-sky regions respectively. After introducing color-lines prior to correct sky regions restored by the dark channel prior, we get an accurate transmission. Finally, the local media mean value and standard deviation are used to refine the transmission to obtain the dehazing image. Experimental results show that the algorithm has obvious advantages in the recovery of the sky area.

scholarly journals ESTIMATING EXTERIOR ORIENTATION PARAMETERS OF HYPERSPECTRAL BANDS BASED ON POLYNOMIAL MODELS

2017 ◽  
Vol XLII-3/W3 ◽  
pp. 19-25 ◽  
Author(s):  
A. Berveglieri ◽  
A. M. G. Tommaselli ◽  
E. Honkavaara
Keyword(s):  
Real Data ◽  
Bundle Adjustment ◽  
Time Dependent ◽  
Camera Model ◽  
Exterior Orientation ◽  
Spectral Bands ◽  
Acquisition Mode ◽  
Polynomial Models ◽  
Orientation Parameters ◽  
Sequential Acquisition

Hyperspectral camera operating in sequential acquisition mode produces spectral bands that are not recorded at the same instant, thus having different exterior orientation parameters (EOPs) for each band. The study presents experiments on bundle adjustment with time-dependent polynomial models for band orientation of hyperspectral cubes sequentially collected. The technique was applied to a Rikola camera model. The purpose was to investigate the behaviour of the estimated polynomial parameters and the feasibility of using a minimum of bands to estimate EOPs. Simulated and real data were produced for the analysis of parameters and accuracy in ground points. The tests considered conventional bundle adjustment and the polynomial models. The results showed that both techniques were comparable, indicating that the time-dependent polynomial model can be used to estimate the EOPs of all spectral bands, without requiring a bundle adjustment of each band. The accuracy of the block adjustment was analysed based on the discrepancy obtained from checkpoints. The root mean square error (RMSE) indicated an accuracy of 1&amp;thinsp;GSD in planimetry and 1.5&amp;thinsp;GSD in altimetry, when using a minimum of four bands per cube.

scholarly journals Objective assessment for characterising the flatness of garment sewing stitches

2013 ◽  
Vol 13 (4) ◽  
pp. 110-117
Author(s):  
Jiang Hongxia ◽  
Liu Jihong ◽  
Chai Zhilei ◽  
Wang Chunxia ◽  
Zhang Mingxia
Keyword(s):  
Standard Deviation ◽  
Empirical Mode Decomposition ◽  
Objective Assessment ◽  
Window Size ◽  
Experimental Results ◽  
Classification Method ◽  
Average Area ◽  
Mode Decomposition ◽  
Two Parameters

Abstract In this paper, a novel classification method of assessing garment sewing stitch based on amended bi-dimensional empirical mode decomposition (ABEMD) has been introduced. Two parameters that characterise garment sewing stitch, average area and standard deviation, have been defined based on the grey value of pixels. Experimental results showed that when the window size is 512×128 pixels with regard to average area, the threshold can be decided as 6.00, 5.50, 5.30 and 4.00 for five different grades , respectively. Meanwhile, with regard to standard deviation, the threshold can be decided as 48.00, 40.00, 30.00 and 20.00, respectively. It is demonstrated that the parameters are effective in discriminating sewing stitch images in terms of the grades when used as inputs for the ABEMD. The performance of the algorithm on different garment status is significantly reliable.

Count Distribution and Precision in X-Ray Fluorescence Analysis

1959 ◽  
Vol 3 ◽  
pp. 95-107 ◽  
Author(s):  
Kurt F.J. Heinrich
Keyword(s):  
Standard Deviation ◽  
Poisson Distribution ◽  
Fluorescence Analysis ◽  
Experimental Results ◽  
X Ray ◽  
Statistical Fluctuations ◽  
Count Distribution ◽  
Analytical Result ◽  
Instrument Reliability

AbstractThe statistical fluctuations of photon counts arediscussedas a factor limiting the precision of the analytical result. Assuming a Poisson distribution, the theoretical standard deviation of the result can be calculated. While this prediction does not consider causes of variation other than the count statistics, it is useful in developing methods and checking instrument reliability. Practical examples using experimental results are given.

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