Using horizontal and vertical building structure to constrain indirect sensor orientation

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This paper presents a method to integrate linear horizontal, vertical and right-angled scene structures into the bundle adjustment of image sequences. An increasing number of airborne image acquisition systems is available and equipped with non-metric small- or medium-frame cameras and no or insufficiently accurate INS devices. In cases where the data is to be used for the production of geo-spatial data, where a certain accuracy and precision is required, an indirect sensor orientation, possibly including self-calibration, needs to be performed. The idea which led to the presented approach is to reduce the number of GCPs necessary for this task by applying the mentioned scene structures. The method directly uses the linear structures, visible at man-made objects as fictive observations within the adjustment, while self-calibration of intrinsic camera parameters and lens distortion is included as well. Experiments with two datasets demonstrate that, through this method, only limited GCP information is required to obtain satisfactory results. In fact, in one experiment using oblique images, several scene constraints were provided and only the datum was defined by ground control. The residuals at check points from this setup were similar to the traditional case where several well-distributed GCPs were available in the scene. In the second experiment the ability of this approach to support the bundle adjustment was shown for a UAV dataset. Although no GCP and camera calibration information was available, the visual inspection of adjusted object points and the residuals at horizontal structures confirmed the ability of the method to align an image block with the structure, as embodied in the defined scene constraints. Despite the convincing outcome of the experiments, it needs to be mentioned that some manual work is still involved in defining the constraints. In future work the issue of automation will be addressed.