• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2689-2708
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• 2016

Multi-camera systems which integrate two or more low-cost digital cameras are adopted to reach higher ground coverage and improve the base-height ratio in low altitude remote sensing. To guarantee accurate multi-camera integration, the geometric relationship among cameras must be determined through platform calibration techniques. This paper proposed a combined two-step platform calibration method. In the first step, the static platform calibration was conducted based on the stable relative orientation constraint and convergent conditions among cameras in static environments. In the second step, a dynamic platform self-calibration approach was proposed based on not only tie points but also straight lines in order to correct the small change of the relative relationship among cameras during dynamic flight. Experiments based on the proposed two-step platform calibration method were carried out with terrestrial and aerial images from a multi-camera system combined with four consumer-grade digital cameras onboard an unmanned aerial vehicle. The experimental results have shown that the proposed platform calibration approach is able to compensate the varied relative relationship during flight, acquiring the mosaicing accuracy of virtual images smaller than 0.5pixel. The proposed approach can be extended for calibrating other low-cost multi-camera system without rigorously mechanical structure.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.3
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• pp.191-204
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• 2014

In recent years, multi-camera systems have been recognized as an affordable alternative for the collection of 3D spatial data from physical surfaces. The collected data can be applied for different mapping(e.g., mobile mapping and mapping inaccessible locations)or metrology applications (e.g., industrial, biomedical, and architectural). In order to fully exploit the potential accuracy of these systems and ensure successful manipulation of the involved cameras, a careful system calibration should be performed prior to the data collection procedure. The calibration of a multi-camera system is accomplished when the individual cameras are calibrated and the geometric relationships among the different system components are defined. In this paper, a new single-step approach is introduced for the calibration of a multi-camera system (i.e., individual camera calibration and estimation of the lever-arm and boresight angles among the system components). In this approach, one of the cameras is set as the reference camera and the system mounting parameters are defined relative to that reference camera. The proposed approach is easy to implement and computationally efficient. The major advantage of this method, when compared to available multi-camera system calibration approaches, is the flexibility of being applied for either directly or indirectly geo-referenced multi-camera systems. The feasibility of the proposed approach is verified through experimental results using real data collected by a newly-developed indirectly geo-referenced multi-camera system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.3
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• pp.205-216
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• 2014

Multi-camera systems have been widely used as cost-effective tools for the collection of geospatial data for various applications. In order to fully achieve the potential accuracy of these systems for object space reconstruction, careful system calibration should be carried out prior to data collection. Since the structural integrity of the involved cameras' components and system mounting parameters cannot be guaranteed over time, multi-camera system should be frequently calibrated to confirm the stability of the estimated parameters. Therefore, automated techniques are needed to facilitate and speed up the system calibration procedure. The automation of the multi-camera system calibration approach, which was proposed in the first part of this paper, is contingent on the automated detection, localization, and identification of the object space signalized targets in the images. In this paper, the automation of the proposed camera calibration procedure through automatic target extraction and labelling approaches will be presented. The introduced automated system calibration procedure is then implemented for a newly-developed multi-camera system while considering the optimum configuration for the data collection. Experimental results from the implemented system calibration procedure are finally presented to verify the feasibility the proposed automated procedure. Qualitative and quantitative evaluation of the estimated system calibration parameters from two-calibration sessions is also presented to confirm the stability of the cameras' interior orientation and system mounting parameters.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.137-148
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• 2004

In this paper, we propose a new camera calibration method for rotating multi-view cameras to generate image-based panoramic 3D Virtual Environment. Since calibration accuracy worsens with an increase in distance between camera and calibration pattern, conventional camera calibration algorithms are not proper for panoramic 3D VE generation. To remedy the problem, a geometric relationship among all lenses of a multi-view camera is used for intra-camera calibration. Another geometric relationship among multiple cameras is used for inter-camera calibration. First camera parameters for all lenses of each multi-view camera we obtained by applying Tsai's algorithm. In intra-camera calibration, the extrinsic parameters are compensated by iteratively reducing discrepancy between estimated and actual distances. Estimated distances are calculated using extrinsic parameters for every lens. Inter-camera calibration arranges multiple cameras in a geometric relationship. It exploits Iterative Closet Point (ICP) algorithm using back-projected 3D point clouds. Finally, by repeatedly applying intra/inter-camera calibration to all lenses of rotating multi-view cameras, we can obtain improved extrinsic parameters at every rotated position for a middle-range distance. Consequently, the proposed method can be applied to stitching of 3D point cloud for panoramic 3D VE generation. Moreover, it may be adopted in various 3D AR applications.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.487-493
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• 1998

Camera calibration is the process of determining the coordinate relationship between a camera image and its real world space. Accurate calibration of a camera is necessary for the applications that involve quantitative measurement of camera images. However, if the camera plane is parallel or near parallel to the calibration board on which 2 dimensional objects are defined(this is called "ill-conditioned"), existing solution procedures are not well applied. In this paper, we propose a neural network-based approach to camera calibration for 2D images formed by a mono-camera or a pair of cameras. Multi-layer perceptrons are developed to transform the coordinates of each image point to the world coordinates. The validity of the approach is tested with data points which cover the whole 2D space concerned. Experimental results for both mono-camera and stereo-camera cases indicate that the proposed approach is comparable to Tsai's method［8］. Especially for the stereo camera case, the approach works better than the Tsai's method as the angle between the camera optical axis and the Z-axis increases. Therefore, we believe the approach could be an alternative solution procedure for the ill -conditioned camera calibration.libration.

• Journal of the Optical Society of Korea
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• v.18 no.6
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• pp.746-752
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• 2014

In a multi-camera measurement system, the determination of the external parameters is one of the vital tasks, referred to as the calibration of the system. In this paper, a new geometrical calibration method, which is based on the theory of the vanishing line, is proposed. Using a planar target with three equally spaced parallel lines, the normal vector of the target plane can be confirmed easily in every camera coordinate system of the measurement system. By moving the target into more than two different positions, the rotation matrix can be determined from related theory, i.e., the expression of the same vector in different coordinate systems. Moreover, the translation matrix can be derived from the known distance between the adjacent parallel lines. In this paper, the main factors effecting the calibration are analyzed. Simulations show that the proposed method achieves robustness and accuracy. Experimental results show that the calibration can reach 1.25 mm with the range about 0.5m. Furthermore, this calibration method also can be used for auto-calibration of the multi-camera mefasurement system as the feature of parallels exists widely.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.187-190
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• 2003

In this paper, we propose an extrinsic calibration method for a multi-view camera to get an optimal pose in 3D space. Conventional calibration algorithms do not guarantee the calibration accuracy at a mid/long distance because pixel errors increase as the distance between camera and pattern goes far. To compensate for the calibration errors, firstly, we apply the Tsai's algorithm to each lens so that we obtain initial extrinsic parameters Then, we estimate extrinsic parameters by using distance vectors obtained from structural cues of a multi-view camera. After we get the estimated extrinsic parameters of each lens, we carry out a non-linear optimization using the relationship between camera coordinate and world coordinate iteratively. The optimal camera parameters can be used in generating 3D panoramic virtual environment and supporting AR applications.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.250-255
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• 2003

The position of a 3-dimensional(3D) point can be measured by using calibrated stereo camera. To obtain more accurate measurement ,more accurate camera calibration is required. There are many existing methods to calibrate camera. The simple linear methods are usually not accurate due to nonlinear lens distortion. The nonlinear methods are accurate more than linear method, but it increase computational cost and good initial guess is needed. The multi step methods need to know some camera parameters of used camera. Recent years, these explicit model based camera calibration work with the development of more precise camera models involving correction of lens distortion. But these explicit model based camera calibration have disadvantages. So implicit camera calibration methods have been derived. One of the popular implicit camera calibration method is to use neural network. In this paper, we propose implicit stereo camera calibration method for 3D reconstruction using support vector machine. SVM can learn the relationship between 3D coordinate and image coordinate, and it shows the robust property with the presence of noise and lens distortion, results of simulation are shown in section 4.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.2
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• pp.67-76
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• 2008

Recently, one of the most outstanding technological characteristics of aerial survey is an application of Direct Georeferencing, which is based on the integration of main sensing sensors such as aerial camera or Lidar with positioning sensors GPS and IMU. In addition, a variety of digital aerial mapping cameras is developed and supplied with the verification of their technical superiority and applicability. In accordance with this requirement, the development of a multi-looking aerial photographing system is just making 3-D information acquisition and texture mapping possible for the dead areas arising from building side and high terrain variation where the use of traditional phptogrammetry is not valid. However, the development of a multi-looking camera integrating different sensors and multi-camera array causes some problems to conduct time synchronization among sensors and their geometric and radiometric calibration. The establishment of a test field for aerial sensor calibration is absolutely necessary to solve this problem. Therefore, this paper describes investigations for photogrammetric Test Field of foreign countries and suggest an establishment scheme for domestic test field.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.129-134
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• 2003

Mobile Mapping System needs system calibration of multi sensors. System calibration is defined as determination of spatial and rotational offsets between the sensors. Especially, EO parameters of GPS/INS require knowledge of the calibration to camera frame. The calibration parameters must be determined with the highest achievable accuracy in order to get 3D coordinate points in stereo CCD images. This study applies Boresight calibration for the calibration between GPS/INS and camera, and estimates the Performance of the calibration.