Geometric camera calibration using circular control points

2000 ◽  
Vol 22 (10) ◽  
pp. 1066-1077 ◽  
Author(s):  
J. Heikkila
Keyword(s):  
Camera Calibration ◽  
Control Points

scholarly journals 3D THERMAL MAPPING OF BUILDING ROOFS BASED ON FUSION OF THERMAL AND VISIBLE POINT CLOUDS IN UAV IMAGERY

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 271-277
Author(s):  
M. Dahaghin ◽  
F. Samadzadegan ◽  
F. Dadras Javan
Keyword(s):  
Camera Calibration ◽  
Point Cloud ◽  
Point Clouds ◽  
Control Points ◽  
Thermal Camera ◽  
Dense Point ◽  
Normal Vectors ◽  
Projection Error ◽  
Orientation Parameters ◽  
Vegetation Layer

Abstract. Thermography is a robust method for detecting thermal irregularities on the roof of the buildings as one of the main energy dissipation parts. Recently, UAVs are presented to be useful in gathering 3D thermal data of the building roofs. In this topic, the low spatial resolution of thermal imagery is a challenge which leads to a sparse resolution in point clouds. This paper suggests the fusion of visible and thermal point clouds to generate a high-resolution thermal point cloud of the building roofs. For the purpose, camera calibration is performed to obtain internal orientation parameters, and then thermal point clouds and visible point clouds are generated. In the next step, both two point clouds are geo-referenced by control points. To extract building roofs from the visible point cloud, CSF ground filtering is applied, and the vegetation layer is removed by RGBVI index. Afterward, a predefined threshold is applied to the normal vectors in the z-direction in order to separate facets of roofs from the walls. Finally, the visible point cloud of the building roofs and registered thermal point cloud are combined and generate a fused dense point cloud. Results show mean re-projection error of 0.31 pixels for thermal camera calibration and mean absolute distance of 0.2 m for point clouds registration. The final product is a fused point cloud, which its density improves up to twice of the initial thermal point cloud density and it has the spatial accuracy of visible point cloud along with thermal information of the building roofs.

scholarly journals STUDY OF THE INTEGRATION OF LIDAR AND PHOTOGRAMMETRIC DATASETS BY <i>IN SITU</i> CAMERA CALIBRATION AND INTEGRATED SENSOR ORIENTATION

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 647-652 ◽  
Author(s):  
E. Mitishita ◽  
F. Costa ◽  
M. Martins
Keyword(s):  
Camera Calibration ◽  
Control Points ◽  
Engineering Project ◽  
Integrated Sensor ◽  
Common Procedure ◽  
Sensor Orientation ◽  
The Moment ◽  
High Degree

Photogrammetric and Lidar datasets should be in the same mapping or geodetic frame to be used simultaneously in an engineering project. Nowadays direct sensor orientation is a common procedure used in simultaneous photogrammetric and Lidar surveys. Although the direct sensor orientation technologies provide a high degree of automation process due to the GNSS/INS technologies, the accuracies of the results obtained from the photogrammetric and Lidar surveys are dependent on the quality of a group of parameters that models accurately the user conditions of the system at the moment the job is performed. This paper shows the study that was performed to verify the importance of the in situ camera calibration and Integrated Sensor Orientation without control points to increase the accuracies of the photogrammetric and LIDAR datasets integration. The horizontal and vertical accuracies of photogrammetric and Lidar datasets integration by photogrammetric procedure improved significantly when the Integrated Sensor Orientation (ISO) approach was performed using Interior Orientation Parameter (IOP) values estimated from the in situ camera calibration. The horizontal and vertical accuracies, estimated by the Root Mean Square Error (RMSE) of the 3D discrepancies from the Lidar check points, increased around of 37% and 198% respectively.

scholarly journals The New Approach to Camera Calibration – GCPs or TLS Data?

2016 ◽  
Vol XLI-B3 ◽  
pp. 75-82
Author(s):  
J. Markiewicz ◽  
P. Podlasiak ◽  
M. Kowalczyk ◽  
D. Zawieska
Keyword(s):  
Camera Calibration ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Automatic Identification ◽  
Test Field ◽  
Control Points ◽  
Data Set ◽  
Laser Measurements ◽  
Close Range ◽  
Processed Products

Camera calibration is one of the basic photogrammetric tasks responsible for the quality of processed products. The majority of calibration is performed with a specially designed test field or during the self-calibration process. The research presented in this paper aims to answer the question of whether it is necessary to use control points designed in the standard way for determination of camera interior orientation parameters. Data from close-range laser scanning can be used as an alternative. The experiments shown in this work demonstrate the potential of laser measurements, since the number of points that may be involved in the calculation is much larger than that of commonly used ground control points. The problem which still exists is the correct and automatic identification of object details in the image, taken with a tested camera, as well as in the data set registered with the laser scanner.

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