Traditional methods for geometrical camera calibration are based on calibration grids or single pixel illumination by collimated light. A new method for geometrical sensor calibration by means of diffractive optical elements (DOE) in connection with a laser beam equipment is presented. This method can be especially used for 2D-sensor array systems but in principle also for line scanners.
<p><strong>Abstract.</strong> Geometric camera calibration is a mandatory prerequisite for many applications in computer vision and photogrammetry. Especially when requiring an accurate camera model the effort for calibration can increase dramatically. For the calibration of the stereo-camera used for optical navigation a new chessboard based approach is presented. It is derived from different parts of existing approaches which, taken separately, are not able to meet the requirements. Moreover, the approach adds one novel main feature: It is able to detect all visible chessboard fields with the help of one or more fiducial markers simply sticked on a chessboard (AprilTags). This allows a robust detection of one or more chessboards in a scene, even from extreme perspectives. Except for the acquisition of the calibration images the presented approach enables a fully automatic calibration. Together with the parameters of the interior and relative orientation the full covariance matrix of all model parameters is calculated and provided, allowing a consistent error propagation in the whole processing chain of the imaging system. Even though the main use case for the approach is a stereo camera system it can be used for a multi-camera system with any number of cameras mounted on a rigid frame.</p>
ABSTRACT:Vision-aided inertial navigation is a navigation method which combines inertial navigation with computer vision techniques. It can provide a six degrees of freedom navigation solution from passive measurements without external referencing (e.g. GPS). Thus, it can operate in unknown environments without any prior knowledge. Such a system, called IPS (Integrated Positioning System) is developed by the German Aerospace Center (DLR). For optical navigation applications, a reliable and efficient feature detector is a crucial component. With the publication of AGAST, a new feature detector has been presented, which is faster than other feature detectors. To apply AGAST to optical navigation applications, we propose several methods to improve its performance. Based on a new non-maximum suppression algorithm, automatic threshold adaption algorithm in combination with an image split method, the optimized AGAST provides higher reliability and efficiency than the original implementation using the Kanade Lucas Tomasi (KLT) feature detector. Finally, we compare the performance of the optimized AGAST with the KLT feature detector in the context of IPS. The presented approach is tested using real data from typical indoor scenes, evaluated on the accuracy of the navigation solution. The comparison demonstrates a significant performance improvement achieved by the optimized AGAST.
<p><strong>Abstract.</strong> This paper presents a laboratory approach for geometric calibration of airborne camera systems. The setup uses an incoming laser beam, which is split by Diffractive Optical Elements (DOE) into a number of beams with precisely-known propagation directions. Each point of the diffraction pattern represents a point at infinity and is invariant against translation. A single image is sufficient to allow a complete camera calibration in accordance with classical camera calibration methods using the pinhole camera model and a distortion model. The presented method is time saving, since complex bundle adjustment procedures with several images are not necessary. It is well suited for the use with frame camera systems, but it works in principle also for pushbroom scanners. In order to prove the reliability, a conventional test field calibration is compared against the presented approach, showing that all estimated camera parameters are just insignificantly different. Furthermore a test flight over the Zeche Zollern reference target has been conducted. The aerotriangulation results shows that calibrating an airborne camera system with DOE is a feasible solution.</p>
Ego localization is an important prerequisite for several scientific, commercial, and statutory tasks. Only by knowing one's own position, can guidance be provided, inspections be executed, and autonomous vehicles be operated. Localization becomes challenging if satellite-based navigation systems are not available, or data quality is not sufficient. To overcome this problem, a team of the German Aerospace Center (DLR) developed a multi-sensor system based on the human head and its navigation sensors -the eyes and the vestibular system. This system is called integrated positioning system (IPS) and contains a stereo camera and an inertial measurement unit for determining an ego pose in six degrees of freedom in a local coordinate system. IPS is able to operate in real time and can be applied for indoor and outdoor scenarios without any external reference or prior knowledge. In this paper, the system and its key hardware and software components are introduced. The main issues during the development of such complex multi-sensor measurement systems are identified and discussed, and the performance of this technology is demonstrated. The developer team started from scratch and transfers this technology into a commercial product right now. The paper finishes with an outlook.
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