Algorithm for determining the orientation elements of an infrared image obtained from a drone using reference points

2020 ◽  
Vol 958 (4) ◽  
pp. 41-50
Author(s):  
S.M. Mokrova ◽  
R.P. Petrov ◽  
V.N. Milich
Keyword(s):  
Focal Length ◽  
Three Dimensional ◽  
Infrared Image ◽  
Image Plane ◽  
Reference Points ◽  
Spatial Coordinates ◽  
Aerial Vehicle ◽  
True Position ◽  
Image Orientation ◽  
Perspective Center

The article deals with the algorithm for determining the exterior and interior orientation elements of an infrared image obtained from an unmanned aerial vehicle using four reference points. The idea of the proposed algorithm is to determine the true position of the image by the defined three-dimensional spatial coordinates of the reference points in the image at the time of shooting. The image plane is built up on the defined points. The coordinates of the principal point of the image are calculated by making a perpendicular from the perspective center to the plane of the image. The focal length is equal to the length of this perpendicular. Euler angles characterizing the position of the camera at the time of shooting are calculated after determining the axes’ directions of the inclined image coordinate system. The proposed algorithm is effective even in the case when all the elements of the image orientation are unknown. Calculations of the image elements on model examples with different initial data show high accuracy. The possibility of obtaining the necessary accuracy for the orthotransformation procedure was confirmed on real images.

scholarly journals GEODESY, CARTOGRAPHY AND AERIAL PHOTOGRAPHY

2020 ◽  
Vol 92,2020 (92) ◽  
pp. 45-54
Author(s):  
V. Hlotov ◽  
◽  
М. Fys ◽  
О. Pashchetnyk ◽  
◽  
...  
Keyword(s):  
Aerial Photography ◽  
Large Scale ◽  
Digital Images ◽  
Optimal Algorithm ◽  
Reference Points ◽  
Practical Significance ◽  
System Of Equations ◽  
First Case ◽  
Spatial Coordinates ◽  
Aerial Vehicle

Purpose. Develop an optimal algorithm that will increase the accuracy of determining the coordinates of the terrain when using the aerial process applying an unmanned aerial vehicle (UAV). Method. The minimization of function based on the condition of collinearity is performed, which clarifies the elements of external orientation (EZO) of digital images and leads to an increase in the accuracy of the spatial coordinates of the points of objects. The proposed function is the sum of the squares of the differences between the calculated and measured reference points on the corresponding digital images. The sequence of implementation of the proposed algorithm is that taking into account the condition of the minimum of this function makes it possible to obtain a system of six nonlinear equations for EZO. The process of determining EZO is performed in two ways: in the first case, the function G is minimized directly by one of the numerical methods, and in the second - obtained as a solution of a system of equations, which gives refined EZO values based on initial approximations obtained directly from UAV telemetry. Modified conditions of the minimum of the function G in which there are no differentiation operations are used to control the accuracy of EZO determination. As a result, we obtain the final values of the EZO at the time of shooting. Results. An algorithm has been developed and tested on mock-ups on real examples, which allows to increase the accuracy of calculating the coordinates of terrain points when using UAVs for the aerial photography process. Scientific novelty. Formulas are obtained, which increase the accuracy of creating topographic materials by digital stereophotogrammetric method. Practical significance. The implementation of the developed algorithm will significantly increase the accuracy of processing large-scale orthophotos and topographic plans created on the basis of aerial photography from UAVs.

Measurements in 3D images

1991 ◽  
Vol 49 ◽  
pp. 408-409
Author(s):  
John C. Russ
Keyword(s):  
Three Dimensional ◽  
Image Plane ◽  
X Rays ◽  
Traditional Use ◽  
3D Images ◽  
Confocal Scanning Laser Microscope ◽  
Hard Materials ◽  
Depth Direction ◽  
Confocal Scanning ◽  
Confocal Scanning Laser

Three-dimensional (3D) images consisting of arrays of voxels can now be routinely obtained from several different types of microscopes. These include both the transmission and emission modes of the confocal scanning laser microscope (but not its most common reflection mode), the secondary ion mass spectrometer, and computed tomography using electrons, X-rays or other signals. Compared to the traditional use of serial sectioning (which includes sequential polishing of hard materials), these newer techniques eliminate difficulties of alignment of slices, and maintain uniform resolution in the depth direction. However, the resolution in the z-direction may be different from that within each image plane, which makes the voxels non-cubic and creates some difficulties for subsequent analysis.

Effect of Field Setup on Accuracy of Traffic Data Collection Using Machine Vision Technology

2002 ◽  
Vol 1804 (1) ◽  
pp. 62-66 ◽  
Author(s):  
Sunita Nadella ◽  
Lloyd A. Herman
Keyword(s):  
Machine Vision ◽  
Focal Length ◽  
Reference Points ◽  
Specific Reference ◽  
Traffic Data ◽  
Video Traffic ◽  
Vertical Angle ◽  
Traffic Data Collection ◽  
Camera Position ◽  
Parameter Ranges

Video traffic data were collected in 24 combinations of four different camera position parameters. A machine vision processor was used to detect vehicle speeds and volumes from the videotapes. The machine vision results were then compared with the actual vehicle volumes and speeds to give the percentage errors in each case. The results of the study provide a procedure with which to establish camera position parameters with specific reference points to help machine vision users select suitable camera positions and develop appropriate measurement error expectations. The camera position parameters that were most likely to produce the least overall volume and speed errors, for the specific site and field setup with the parameter ranges used in this study, were the low height of approximately 7.6 m (25 ft), with an upstream orientation (traffic moving toward the camera), a 50-mm (midangle) focal length, and a 15° vertical angle.

scholarly journals Filtering Biomechanical Signals in Movement Analysis

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4580
Author(s):  
Francesco Crenna ◽  
Giovanni Battista Rossi ◽  
Marta Berardengo
Keyword(s):  
Measurement Uncertainty ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Movement Analysis ◽  
Analytical Signal ◽  
Human Movement ◽  
Reference Points ◽  
Biomechanical Analysis ◽  
Method Performance ◽  
Acceleration Signal

Biomechanical analysis of human movement is based on dynamic measurements of reference points on the subject’s body and orientation measurements of body segments. Collected data include positions’ measurement, in a three-dimensional space. Signal enhancement by proper filtering is often recommended. Velocity and acceleration signal must be obtained from position/angular measurement records, needing numerical processing effort. In this paper, we propose a comparative filtering method study procedure, based on measurement uncertainty related parameters’ set, based upon simulated and experimental signals. The final aim is to propose guidelines to optimize dynamic biomechanical measurement, considering the measurement uncertainty contribution due to the processing method. Performance of the considered methods are examined and compared with an analytical signal, considering both stationary and transient conditions. Finally, four experimental test cases are evaluated at best filtering conditions for measurement uncertainty contributions.

scholarly journals Collaborative Pursuit-Evasion Strategy of UAV/UGV Heterogeneous System in Complex Three-Dimensional Polygonal Environment

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Xiao Liang ◽  
Honglun Wang ◽  
Haitao Luo
Keyword(s):  
Visual Field ◽  
Heterogeneous System ◽  
Three Dimensional ◽  
Unmanned Ground Vehicle ◽  
Worst Case ◽  
Ground Vehicle ◽  
Pursuit Evasion ◽  
Evasion Game ◽  
Evasion Strategy ◽  
Aerial Vehicle

The UAV/UGV heterogeneous system combines the air superiority of UAV (unmanned aerial vehicle) and the ground superiority of UGV (unmanned ground vehicle). The system can complete a series of complex tasks and one of them is pursuit-evasion decision, so a collaborative strategy of UAV/UGV heterogeneous system is proposed to derive a pursuit-evasion game in complex three-dimensional (3D) polygonal environment, which is large enough but with boundary. Firstly, the system and task hypothesis are introduced. Then, an improved boundary value problem (BVP) is used to unify the terrain data of decision and path planning. Under the condition that the evader knows the position of collaborative pursuers at any time but pursuers just have a line-of-sight view, a worst case is analyzed and the strategy between the evader and pursuers is studied. According to the state of evader, the strategy of collaborative pursuers is discussed in three situations: evader is in the visual field of pursuers, evader just disappears from the visual field of pursuers, and the position of evader is completely unknown to pursuers. The simulation results show that the strategy does not guarantee that the pursuers will win the game in complex 3D polygonal environment, but it is optimal in the worst case.

scholarly journals Fast and Robust Orientation of Cryo-Electron Microscopy Images

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Guoliang Xu ◽  
Xia Wang ◽  
Ming Li ◽  
Zhucui Jing
Keyword(s):  
Sparse Matrix ◽  
Three Dimensional ◽  
Image Plane ◽  
Real Space ◽  
Computation Method ◽  
Common Line ◽  
The Matrix ◽  
Common Lines ◽  
The Common ◽  
Dimensional Object

AbstractWe present an efficient and reliable algorithm for determining the orientations of noisy images obtained fromprojections of a three-dimensional object. Based on the linear relationship among the common line vectors in one image plane, we construct a sparse matrix, and show that the coordinates of the common line vectors are the eigenvectors of the matrix with respect to the eigenvalue 1. The projection directions and in-plane rotation angles can be determined fromthese coordinates. A robust computation method of common lines in the real space using aweighted cross-correlation function is proposed to increase the robustness of the algorithm against the noise. A small number of good leading images, which have the maximal dissimilarity, are used to increase the reliability of orientations and improve the efficiency for determining the orientations of all the images. Numerical experiments show that the proposed algorithm is effective and efficient.

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