The publication familiarizes the reader with MicMac -a free, open-source photogrammetric software for 3D reconstruction. A brief history of the tool, its organisation and unique features vis-à-vis other software tools are in the highlight. The essential algorithmic aspects of the structure from motion and image dense matching problems are discussed from the implementation and the user's viewpoints.

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ABS TRACT:The use of oblique imagery has become a standard for many civil and mapping applications, thanks to the development of airborne digital multi-camera systems, as proposed by many companies (Blomoblique, IGI, Leica, M idas, Pictometry, Vexcel/M icrosoft, VisionM ap, etc.). The indisputable virtue of oblique photography lies in its simplicity of interpretation and understanding for inexperienced users allowing their use of oblique images in very different applications, such as building detection and reconstruction, building structural damage classification, road land updating and administration services, etc. The paper reports an overview of the actual oblique commercial systems and presents a workflow for the automated orientation and dense matching of large image blocks. Perspectives, potentialities, pitfalls and suggestions for achieving satisfactory results are given. Tests performed on two datasets acquired with two multi-camera systems over urban areas are also reported.Figure 1: Large urban area pictured with an oblique multi-camera system. Once advanced image triangulation methods have retrieved interior and exterior parameters of the cameras, dense point clouds can be deriv ed for 3D city modelling, feature extraction and mapping purposes.

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Unmanned aerial vehicles (UAV) are increasingly used for topographic mapping. The camera calibration for UAV image blocks can be performed a priori or during the bundle block adjustment (self-calibration). For an area of interest with flat scene and corridor configuration, the focal length of camera is highly correlated with the height of the camera. Furthermore, systematic errors of camera calibration accumulate on the longer dimension and cause deformation. Therefore, special precautions must be taken when estimating camera calibration parameters. In order to better investigate the impact of camera calibration errors, a synthetic, error-free aerial image block is generated to simulate several issues of interest. Firstly, the erroneous focal length in the case of camera pre-calibration is studied. Nadir images are not able to prevent camera poses from drifting to compensate for the erroneous focal length, whereas the inclusion of oblique images brings significant improvement. Secondly, the case where the focal length varies gradually (e.g., when the camera subject to temperature changes) is investigated. The neglect of this phenomenon can substantially degrade the 3D measurement accuracy. Different flight configurations and flight orders are analyzed, the combination of oblique and nadir images shows better performance. At last, the rolling shutter effect is investigated. The influence of camera rotational motion on the final accuracy is negligible compared to that of the translational motion. The acquisition configurations investigated are not able to mitigate the degradation introduced by the rolling shutter effect. Other solutions such as correcting image measurements or including camera motion parameters in the bundle block adjustment should be exploited.

With the development of unmanned aerial vehicles (UAVs) and global navigation satellite system (GNSS), the accurate camera positions at exposure can be known and the GNSS-assisted bundle block adjustment (BBA) approach is possible for integrated sensor orientation (ISO). This study employed ISO approach for camera pose determination with the objective of investigating the impact of a good sensor pre-calibration on a poor acquisition geometry. Within the presented works, several flights were conducted on a dike by a small UAV embedded with a metric camera and a GNSS receiver. The multi-lever-arm estimation within the BBA procedure makes it possible to merge image blocks of different configurations such as nadir and oblique images without physical constraints on camera and GNSS antenna positions. The merged image block achieves a better accuracy and the sensor self-calibrated well. The issued sensor calibration is then applied to a less preferable acquisition configuration and the accuracy is significantly improved. For a corridor acquisition scene of about 600 m, a centimetric accuracy is reached with one GCP. With the provided sensor pre-calibration, an accuracy of 3.9 normalcnormalm is achieved without any GCP.

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ABSTRACT:Nowadays, multi-camera platforms combining nadir and oblique cameras are experiencing a revival. Due to their advantages such as ease of interpretation, completeness through mitigation of occluding areas, as well as system accessibility, they have found their place in numerous civil applications. However, automatic post-processing of such imagery still remains a topic of research. Configuration of cameras poses a challenge on the traditional photogrammetric pipeline used in commercial software and manual measurements are inevitable. For large image blocks it is certainly an impediment. Within theoretical part of the work we review three common least square adjustment methods and recap on possible ways for a multi-camera system orientation. In the practical part we present an approach that successfully oriented a block of 550 images acquired with an imaging system composed of 5 cameras (Canon Eos 1D Mark III) with different focal lengths. Oblique cameras are rotated in the four looking directions (forward, backward, left and right) by 45• with respect to the nadir camera. The workflow relies only upon open-source software: a developed tool to analyse image connectivity and Apero to orient the image block. The benefits of the connectivity tool are twofold: in terms of computational time and success of Bundle Block Adjustment. It exploits the georeferenced information provided by the Applanix system in constraining feature point extraction to relevant images only, and guides the concatenation of images during the relative orientation. Ultimately an absolute transformation is performed resulting in mean re-projection residuals equal to 0.6pix.