Ewelina Rupnik
Kessler Foundation
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Publication
Featured researches published by Ewelina Rupnik.
Open Geospatial Data, Software and Standards | 2017
Ewelina Rupnik; Mehdi Daakir; Marc Pierrot Deseilligny
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.
Open Geospatial Data, Software and Standards | 2017
Oscar Martinez-Rubi; Francesco Carlo Nex; Marc Pierrot-Deseilligny; Ewelina Rupnik
BackgroundIn the last decade Photogrammetry has shown to be a valid alternative to LiDAR techniques for the generation of dense point clouds in many applications. However, dealing with large image sets is computationally demanding. It requires high performance hardware and often long processing times that makes the photogrammetric point cloud generation not suitable for mapping purposes at regional and national scale. These limitations are partially overcome by commercial solutions, thanks to the use of expensive and dedicated hardware. Nonetheless, a Free and Open-Source Software (FOSS) photogrammetric solution able to cope with these limitations is still missing.MethodsIn this paper, the bottlenecks of the basic components of photogrammetric workflows -tie-points extraction, bundle block adjustment (BBA) and dense image matching- are tackled implementing FOSS solutions. We present distributed computing algorithms for the tie-points extraction and for the dense image matching. Moreover, we present two algorithms for decreasing the memory needs of the BBA. The various algorithms are deployed on different hardware systems including a computer cluster.Results and conclusionsThe usage of the algorithms presented allows to process large image sets reducing the computational time. This is demonstrated using two different datasets.
Sensors | 2018
Nguyen Truong Giang; Jean-Michaël Muller; Ewelina Rupnik; Christian Thom; Marc Pierrot-Deseilligny
Photogrammetric processing is available in various software solutions and can easily deliver 3D pointclouds as accurate as 1 pixel. Certain applications, e.g., very accurate shape reconstruction in industrial metrology or change detection for deformation studies in geosciences, require results of enhanced accuracy. The tie-point extraction step is the opening in the photogrammetric processing chain and therefore plays a key role in the quality of the subsequent image orientation, camera calibration and 3D reconstruction. Improving its precision will have an impact on the obtained 3D. In this research work we describe a method which aims at enhancing the accuracy of image orientation by adding a second iteration photogrammetric processing. The result from the classical processing is used as a priori information to guide the extraction of refined tie-points of better photogrammetric quality. Evaluated on indoor and UAV acquisitions, the proposed methodology shows a significant improvement on the obtained 3D point accuracy.
European Journal of Remote Sensing | 2018
Ewelina Rupnik; Francesco Carlo Nex; I. Toschi; Fabio Remondino
ABSTRACT This research presents a processing workflow to automatically find damaged building areas in an urban context. The input data requirements are high-resolution multi-view images, acquired from airborne platform. The elevations are derived from a dense surface model generated with photogrammetric methods. With the principal objective of rapid response in emergency situations, two different processing roadmaps are proposed, semi-supervised and unsupervised. Both of them follow a two-step workflow of building detection and building health estimation. Optionally, cadastral layers may serve as a-priori knowledge on building location. The semi-supervised approach involves a data training step, while the unsupervised approach exploits the similarities and dissimilarities between sets of features calculated over the detected buildings. The change detection task is formulated as a classification task defined over a conditional random field. The algorithms are evaluated using two datasets (Vexcel and Midas cameras) and results are compared with ground truth data and specific metrics.
Sensors | 2015
Ewelina Rupnik; Josef Jansa; Norbert Pfeifer
The objective of the work is to model the shape of the sinusoidal shape of regular water waves generated in a laboratory flume. The waves are traveling in time and render a smooth surface, with no white caps or foam. Two methods are proposed, treating the water as a diffuse and specular surface, respectively. In either case, the water is presumed to take the shape of a traveling sine wave, reducing the task of the 3D reconstruction to resolve the wave parameters. The first conceived method performs the modeling part purely in 3D space. Having triangulated the points in a separate phase via bundle adjustment, a sine wave is fitted into the data in a least squares manner. The second method presents a more complete approach for the entire calculation workflow beginning in the image space. The water is perceived as a specular surface, and the traveling specularities are the only observations visible to the cameras, observations that are notably single image. The depth ambiguity is removed given additional constraints encoded within the law of reflection and the modeled parametric surface. The observation and constraint equations compose a single system of equations that is solved with the method of least squares adjustment. The devised approaches are validated against the data coming from a capacitive level sensor and on physical targets floating on the surface. The outcomes agree to a high degree.
Videometrics, Range Imaging, and Applications XII; and Automated Visual Inspection | 2013
Ewelina Rupnik; Josef Jansa
Central to our investigation is determination of dynamic behaviour of a highly reflective platform floating on water, as well as derivation of parameters defining instantaneous water state. The employed imaging setup consists of three off-the-shelf dSLR cameras capable of video recording at a 30Hz frame rate. In order to observe a change, the non-rigid and non-diffuse bodies impose the adoption of artificial targetting and custom measurement algorithms. Attention will be given to an in-house software tool implemented to carry out point measurement, correspondence search, tracking and outlier detection methods in the presence of specular reflections and a multimedia scene. A methodology for retrieval of wave parameters in regular wave conditions is also automatically handled by the software and will be discussed. In the context of performed measurements and achieved results, we will point out the extent to which consumer grade camera can fulfil automation and accuracy demands of industrial applications and the pitfalls entailed. Lastly, we will elaborate on visual representation of computed motion and deformations.
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences | 2014
Ewelina Rupnik; Francesco Carlo Nex; Fabio Remondino
Isprs Journal of Photogrammetry and Remote Sensing | 2015
Ewelina Rupnik; Francesco Carlo Nex; I. Toschi; Fabio Remondino
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences | 2014
A. Murtiyoso; Fabio Remondino; Ewelina Rupnik; Francesco Carlo Nex; Pierre Grussenmeyer
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences | 2014
Francesco Carlo Nex; Ewelina Rupnik; I. Toschi; Fabio Remondino