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.

ABSTRACT:IGN has developed a set of photogrammetric tools, APERO and MICMAC, for computing 3D models from set of images. This software, developed initially for its internal needs are now delivered as open source code. This paper focuses on the presentation of APERO the orientation software. Compared to some other free software initiatives, it is probably more complex but also more complete, its targeted user is rather professionals (architects, archaeologist, geomophologist) than people. APERO uses both computer vision approach for estimation of initial solution and photogrammetry for a rigorous compensation of the total error; it has a large library of parametric model of distortion allowing a precise modelization of all the kind of pinhole camera we know, including several model of fish-eye; there is also several tools for geo-referencing the result. The results are illustrated on various application, including the data-set of 3D-Arch workshop.

ABSTRACT:This publication presents the RPC-based bundle adjustment implemented in the freeware open-source photogrammetric tool Apero/MicMac. The bundle adjustment model is based on some polynomial correction functions, enriched with a physical constraint that introduces the notion of a global sensor rotation into the model. The devised algorithms are evaluated against two datasets consisting of two stereo and a triplet pair of the Pleiades images. Two sets of correction functions and a number of GCPs configurations are examined. The obtained geo-referencing accuracy falls below the size of 1GSD.

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This paper presents a new method for improving the geometric accuracy of photogrammetric reconstruction by modeling and correcting the thermal effect on camera image sensor. The objective is to verify that when the temperature of image sensor varies during the acquisition, image deformation induced by the temperature change is quantifiable, modelisable and correctable. A temperature sensor integrated in the camera enables the measurement of image sensor temperature at exposure. It is therefore natural and appropriate to take this effect into account and to finally model and correct it after a calibration step. Nowadays, in cartography applications performed with UAV, the frame rate of acquisitions is continuously increasing. A high frame rate over a long acquisition time can result in an important temperature increase of the image sensor and thus introduces image deformations. The correction of the above-mentioned effect can improve the measurement accuracy. We present three methods to calibrate the thermal effect and experiments on two datasets are carried out to verify the improvement in terms of the photogrammetric accuracy.

ABSTRACT:This publication presents the RPC-based bundle adjustment implemented in the freeware open-source photogrammetric tool Apero/MicMac. The bundle adjustment model is based on some polynomial correction functions, enriched with a physical constraint that introduces the notion of a global sensor rotation into the model. The devised algorithms are evaluated against two datasets consisting of two stereo and a triplet pair of the Pleiades images. Two sets of correction functions and a number of GCPs configurations are examined. The obtained geo-referencing accuracy falls below the size of 1GSD.

ABSTRACT:Due to the increasing number of low-cost sensors, widely accessible on the market, and because of the supposed granted correctness of the semi-automatic workflow for 3D reconstruction, highly implemented in the recent commercial software, more and more users operate nowadays without following the rigorousness of classical photogrammetric methods. This behaviour often naively leads to 3D products that lacks metric quality assessment. This paper proposes and analyses an approach that gives the users the possibility to preserve the trustworthiness of the metric information inherent in the 3D model, without sacrificing the automation offered by modern photogrammetry software. At the beginning, the importance of Data Quality Assessment is outlined, together with some recall of photogrammetry best practices. With the purpose of guiding the user through a correct pipeline for a certified 3D model reconstruction, an operative workflow is proposed, focusing on the first part of the object reconstruction steps (tie-points extraction, camera calibration, and relative orientation). A new GUI (Graphical User Interface) developed for the open source MicMac suite is then presented, and a sample dataset is used for the evaluation of the photogrammetric block orientation using statistically obtained quality descriptors. The results and the future directions are then presented and discussed.