Evaluation of Test Field-based Calibration and Self-calibration Models of UAV Integrated Compact Cameras

The process and definition of camera calibration have change greatly over recent years. Aerial metric cameras calibration, for which laboratory and field calibration procedures were a separate process, was performed before and independent of any actual mapping data collection using precise calibration fixtures with an assumption that the camera parameters determined would remain valid for a significant period. In contrast, non-metric cameras are characterized by unstable intrinsic parameters over the times and they are vulnerable to the engine and other vibrations during flight data acquisitions. Moreover, there is no standard calibration procedures exist for these cameras. But, since non-metric camera self-calibration augments the concept of calibration as a part of the measurement process, it can determine the camera intrinsic parameters at the time of the data acquisition as long as highly-convergent geometry and the use of multiple exposures are employed. Therefore, this paper investigates variations of the lens distortion components with object distance within the photographic field by using the self-calibration method. The use of redundant flight paths and tilted camera is also incorporated to ascertain the stability of the principal distance and the principal points during the flight mission. During the experiments, a series of flight mission is conducted to photograph test field areas from over a relatively flat area to highly mountainous one. It is revealed that the radial, decentering, and affinity distortion parameters are more stable than that of the principal distance and principal points against vibrations.

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SEMANTIC ROAD SCENE KNOWLEDGE FOR ROBUST SELF-CALIBRATION OF ENVIRONMENT-OBSERVING VEHICLE CAMERAS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-w16-103-2019 ◽

2019 ◽

Vol XLII-2/W16 ◽

pp. 103-110

Author(s):

A. Hanel ◽

U. Stilla

Keyword(s):

Moving Objects ◽

Semantic Segmentation ◽

Negative Influence ◽

Semantic Knowledge ◽

Test Field ◽

The Road ◽

Self Calibration ◽

Feature Based ◽

Distortion Parameters ◽

Correspondence Search

<p><strong>Abstract.</strong> Environment-observing vehicle camera self-calibration using a structure from motion (SfM) algorithm allows calibration over vehicle lifetime without the need of special calibration objects being present in the calibration images. Scene-specific problems with feature-based correspondence search and reconstruction during the SfM pipeline might be caused by critical objects like moving objects, poor-texture objects or reflecting objects and might have negative influence on camera calibration. In this contribution, a method to use semantic road scene knowledge by means of semantic masks for a semantic-guided SfM algorithm is proposed to make the calibration more robust. Semantic masks are used to exclude image parts showing critical objects from feature extraction, whereby semantic knowledge is obtained by semantic segmentation of the road scene images. The proposed method is tested with an image sequence recorded in a suburban road scene. It has been shown that semantic guidance leads to smaller deviations of the estimated interior orientation and distortion parameters from reference values obtained by test field calibration compared to a standard SfM algorithm.</p>

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INTERACTION BETWEEN DIRECT GEOREFERENCING, CONTROL POINT CONFIGURATION AND CAMERA SELF-CALIBRATION FOR RTK-BASED UAV PHOTOGRAMMETRY

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliii-b1-2020-485-2020 ◽

2020 ◽

Vol XLIII-B1-2020 ◽

pp. 485-492 ◽

Cited By ~ 1

Author(s):

H.-J. Przybilla ◽

M. Bäumker ◽

T. Luhmann ◽

H. Hastedt ◽

M. Eilers

Keyword(s):

Case Studies ◽

Control Point ◽

Test Field ◽

Lower Saxony ◽

Flight Pattern ◽

Self Calibration ◽

Software Packages ◽

Market Leader ◽

Uav Image ◽

Soil Movements

Abstract. Unmanned Aerial Vehicles (UAV) are enjoying increasing popularity in the photogrammetric community. The Chinese supplier DJI is the market leader with about 70% of the global consumer UAV market. The Phantom model has been available for more than 10 years and its current version "RTK" is equipped with a 2-frequency GNSS receiver, as a basis for direct georeferencing of image flights, using RTK or PPK technologies.In the context of the paper, different case studies are investigated, which allow statements on the geometric accuracy of UAV image flights as well as on the self-calibration of the camera systems.In the first example, four DJI Phantom 4 RTK systems are examined, which were flown in a cross flight pattern configuration on the area of the UAV test field "Zeche Zollern" in Dortmund, Germany. The second example analyses the results of an open moorland area where the establishment of GCPs is extremely difficult and expensive, hence direct georeferencing offers a promising way to evaluate deformations, soil movements or mass calculations. In this example a DJI Matrice 210 v2 RTK drone has been used and the results of two different software packages (Agisoft Metashape and RealityCapture) are analysed. The third example presents a reference building that has been established by the Lower Saxony administration for geoinformation in order to evaluate UAV photogrammetry for cadastral purposes. Here again a DJI Phantom 4 RTK has been tested in a variety of flight configurations and a large number of high precision ground control and check points.The case studies show that the RTK option leads to sufficient results if at least 1 GCP is introduced. Flights without any GCPs lead to a significant height error in the order of up to 30 GSD.

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INVESTIGATION OF PHOTOTRIANGULATION ACCURACY WITH USING OF VARIOUS TECHNIQUES LABORATORY AND FIELD CALIBRATION

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b1-1227-2016 ◽

2016 ◽

Vol XLI-B1 ◽

pp. 1227-1233 ◽

Cited By ~ 1

Author(s):

A. G. Chibunichev ◽

V. M. Kurkov ◽

A. V. Smirnov ◽

A. V. Govorov ◽

V. A. Mikhalin

Keyword(s):

Aerial Survey ◽

Test Field ◽

Control Points ◽

Digital Cameras ◽

Field Calibration ◽

Self Calibration ◽

Practical Research ◽

Calibration Techniques ◽

Aerial Systems ◽

Practical Recommendations

Nowadays, aerial survey technology using aerial systems based on unmanned aerial vehicles (UAVs) becomes more popular. UAVs physically can not carry professional aerocameras. Consumer digital cameras are used instead. Such cameras usually have rolling, lamellar or global shutter. Quite often manufacturers and users of such aerial systems do not use camera calibration. In this case self-calibration techniques are used. However such approach is not confirmed by extensive theoretical and practical research. In this paper we compare results of phototriangulation based on laboratory, test-field or self-calibration. For investigations we use Zaoksky test area as an experimental field provided dense network of target and natural control points. Racurs PHOTOMOD and Agisoft PhotoScan software were used in evaluation. The results of investigations, conclusions and practical recommendations are presented in this article.

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3D Calibration Test-Field for Digital Cameras Mounted on Unmanned Aerial Systems (UAS)

Remote Sensing ◽

10.3390/rs10122017 ◽

2018 ◽

Vol 10 (12) ◽

pp. 2017 ◽

Cited By ~ 6

Author(s):

Valeria-Ersilia Oniga ◽

Norbert Pfeifer ◽

Ana-Maria Loghin

Keyword(s):

Near Infrared ◽

Low Cost ◽

Digital Camera ◽

Field Measurements ◽

Unmanned Aerial Systems ◽

Test Field ◽

Digital Cameras ◽

Self Calibration ◽

Technological Developments ◽

Aerial Systems

Due to the large number of technological developments in recent years, UAS systems are now used for monitoring purposes and in projects with high precision demand, such as 3D model-based creation of dams, reservoirs, historical monuments etc. These unmanned systems are usually equipped with an automatic pilot device and a digital camera (photo/video, multispectral, Near Infrared etc.), of which the lens has distortions; but this can be determined in a calibration process. Currently, a method of “self-calibration” is used for the calibration of the digital cameras mounted on UASs, but, by using the method of calibration based on a 3D calibration object, the accuracy is improved in comparison with other methods. Thus, this paper has the objective of establishing a 3D calibration field for the digital cameras mounted on UASs in terms of accuracy and robustness, being the largest reported publication to date. In order to test the proposed calibration field, a digital camera mounted on a low-cost UAS was calibrated at three different heights: 23 m, 28 m, and 35 m, using two configurations for image acquisition. Then, a comparison was made between the residuals obtained for a number of 100 Check Points (CPs) using self-calibration and test-field calibration, while the number of Ground Control Points (GCPs) variedand the heights were interchanged. Additionally, the parameters where tested on an oblique flight done 2 years before calibration, in manual mode at a medium altitude of 28 m height. For all tests done in the case of the double grid nadiral flight, the parameters calculated with the proposed 3D field improved the results by more than 50% when using the optimum and a large number of GCPs, and in all analyzed cases with 75% to 95% when using a minimum of 3 GCP. In this context, it is necessary to conduct accurate calibration in order to increase the accuracy of the UAS projects, and also to reduce field measurements.

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