Autonomous initialisation of exterior orientation parameters using a collinearity search-based solution

2008 ◽  
Vol 23 (121) ◽  
pp. 90-108
Author(s):  
Gamal H. Seedahmed
Author(s):  
A. Berveglieri ◽  
A. M. G. Tommaselli ◽  
E. Honkavaara

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 GSD in planimetry and 1.5 GSD in altimetry, when using a minimum of four bands per cube.


2020 ◽  
Vol 12 (18) ◽  
pp. 2923
Author(s):  
Tengfei Zhou ◽  
Xiaojun Cheng ◽  
Peng Lin ◽  
Zhenlun Wu ◽  
Ensheng Liu

Due to the existence of environmental or human factors, and because of the instrument itself, there are many uncertainties in point clouds, which directly affect the data quality and the accuracy of subsequent processing, such as point cloud segmentation, 3D modeling, etc. In this paper, to address this problem, stochastic information of point cloud coordinates is taken into account, and on the basis of the scanner observation principle within the Gauss–Helmert model, a novel general point-based self-calibration method is developed for terrestrial laser scanners, incorporating both five additional parameters and six exterior orientation parameters. For cases where the instrument accuracy is different from the nominal ones, the variance component estimation algorithm is implemented for reweighting the outliers after the residual errors of observations obtained. Considering that the proposed method essentially is a nonlinear model, the Gauss–Newton iteration method is applied to derive the solutions of additional parameters and exterior orientation parameters. We conducted experiments using simulated and real data and compared them with those two existing methods. The experimental results showed that the proposed method could improve the point accuracy from 10−4 to 10−8 (a priori known) and 10−7 (a priori unknown), and reduced the correlation among the parameters (approximately 60% of volume). However, it is undeniable that some correlations increased instead, which is the limitation of the general method.


Author(s):  
I.-C. Lee ◽  
F. Tsai

A series of panoramic images are usually used to generate a 720° panorama image. Although panoramic images are typically used for establishing tour guiding systems, in this research, we demonstrate the potential of using panoramic images acquired from multiple sites to create not only 720° panorama, but also three-dimensional (3D) point clouds and 3D indoor models. Since 3D modeling is one of the goals of this research, the location of the panoramic sites needed to be carefully planned in order to maintain a robust result for close-range photogrammetry. After the images are acquired, panoramic images are processed into 720° panoramas, and these panoramas which can be used directly as panorama guiding systems or other applications. <br><br> In addition to these straightforward applications, interior orientation parameters can also be estimated while generating 720° panorama. These parameters are focal length, principle point, and lens radial distortion. The panoramic images can then be processed with closerange photogrammetry procedures to extract the exterior orientation parameters and generate 3D point clouds. In this research, VisaulSFM, a structure from motion software is used to estimate the exterior orientation, and CMVS toolkit is used to generate 3D point clouds. Next, the 3D point clouds are used as references to create building interior models. In this research, Trimble Sketchup was used to build the model, and the 3D point cloud was added to the determining of locations of building objects using plane finding procedure. In the texturing process, the panorama images are used as the data source for creating model textures. This 3D indoor model was used as an Augmented Reality model replacing a guide map or a floor plan commonly used in an on-line touring guide system. <br><br> The 3D indoor model generating procedure has been utilized in two research projects: a cultural heritage site at Kinmen, and Taipei Main Station pedestrian zone guidance and navigation system. The results presented in this paper demonstrate the potential of using panoramic images to generate 3D point clouds and 3D models. However, it is currently a manual and labor-intensive process. A research is being carried out to Increase the degree of automation of these procedures.


Author(s):  
P. C. Lim ◽  
J. Seo ◽  
J. Son ◽  
T. Kim

<p><strong>Abstract.</strong> Utilization of an UAV is increasing because of its easy operation and time saving advantages. Compared with other remote sensing platforms, the biggest difference of a small UAV is the unstable flight attitude due to platform stability. UAVs are equipped with a commercial grade camera, unlike expensive cameras mounted on manned aircraft or satellite platforms. The quality of the map is determined by the characteristics of an UAV and camera performance. In this study, the accuracy of orientation parameters according to UAV camera calibration options was analysed. The camera calibration options were no calibration, self-calibration and calibration by a public calibration toolkit with manual corner measurement. We used four different type of UAVs and three type of SWs. Interior and exterior orientation parameters according to the camera calibration options were obtained from each software. The result of processing by each camera calibration option was different from each other. This may indicate that the UAV camera calibration was not performed accurately and still needed further improvement.</p>


2020 ◽  
Vol 12 (18) ◽  
pp. 3002
Author(s):  
Petra Helmholz ◽  
Derek D. Lichti

The number of researchers utilising imagery for the 3D reconstruction of underwater natural (e.g., reefs) and man-made structures (e.g., shipwrecks) is increasing. Often, the same procedures and software solutions are used for processing the images as in-air without considering additional aberrations that can be caused by the change of the medium from air to water. For instance, several publications mention the presence of chromatic aberration (CA). The aim of this paper is to investigate CA effects in low-cost camera systems (several GoPro cameras) operated in an underwater environment. We found that underwater and in-air distortion profiles differed by more than 1000 times in terms of maximum displacement and in terms of curvature. Moreover, significant CA effects were found in the underwater profiles that did not exist in-air. Furthermore, the paper investigates the effect of adjustment constraints imposed on the underwater self-calibration and the reliability of the interior orientation parameters. The analysis of the precision shows that in-air RMS values are just due to random errors. In contrast, the underwater calibration RMS values are 3x-6x higher than the exterior orientation parameter (EOP) precision, so these values contain both random error and the systematic effects from the CA. The accuracy assessment shows significant differences.


2015 ◽  
Vol 41 (2) ◽  
pp. 66-73 ◽  
Author(s):  
Khalid L. A. El-Ashmawy

The present work emphasizes on using collinearity condition, coplanarity condition and DLT method for determining the camera exterior orientation parameters. The derivation of the mathematical formulation based on each suggested methods is explained. The comparison of the results of the methods was performed based on accuracy aspects using mathematical and actual photogrammetric data. The used data shows that the suggested methods are suitable for camera exterior orientation parameters determination for a block of photographs of any size. The results of this investigation prove that the accuracy of using coplanarity equations is slightly better than using collinearity equations or DLT method. Although the results of the DLT method are less accurate than those of using collinearity or coplanarity equation, DLT method is essential when the necessary information for the collinearity or coplanarity model is not available. This paper shows the necessity for the mathematical photogrammetric data for testing the photogrammetric studies.


2013 ◽  
Vol 389 ◽  
pp. 941-947
Author(s):  
Yu Long Li ◽  
Peng Sun ◽  
Ming Li Dong

A new calibration method for camera interior orientation parameters is proposed using the known spatial coordinates and the corresponding single photo. Firstly, principle point coordinates, principle distance and exterior orientation parameters are solved by the direct linear method without consideration of distortion parameters. Then, accurate interior and exterior orientation parameters are refined through the process of nonlinear optimization, during which the distance of spatial point to corresponding ray are minimized. Distortion factors of radial distortion, tangential distortion, affine distortion and non-orthogonal distortion are taken into consideration. This paper uses Levenberg-Marquardt optimization method to avoid inaccurate initial parameters influence upon the process of convergence.


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