Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/157998
Title: Point Cloud Stacking: A Workflow to Enhance 3D Monitoring Capabilities Using Time-Lapse Cameras
Author: Blanch Gorriz, Xabier
Abellán Fernández, Antonio
Guinau Sellés, Marta
Keywords: Lectors òptics
Fotogrametria
Vigilància electrònica
Optical scanners
Photogrammetry
Electronic surveillance
Issue Date: 13-Apr-2020
Publisher: MDPI
Abstract: The emerging use of photogrammetric point clouds in three-dimensional (3D) monitoring processes has revealed some constraints with respect to the use of LiDAR point clouds. Oftentimes, point clouds (PC) obtained by time-lapse photogrammetry have lower density and precision, especially when Ground Control Points (GCPs) are not available or the camera system cannot be properly calibrated. This paper presents a new workflow called Point Cloud Stacking (PCStacking) that overcomes these restrictions by making the most of the iterative solutions in both camera position estimation and internal calibration parameters that are obtained during bundle adjustment. The basic principle of the stacking algorithm is straightforward: it computes the median of the Z coordinates of each point for multiple photogrammetric models to give a resulting PC with a greater precision than any of the individual PC. The different models are reconstructed from images taken simultaneously from, at least, five points of view, reducing the systematic errors associated with the photogrammetric reconstruction workflow. The algorithm was tested using both a synthetic point cloud and a real 3D dataset from a rock cliff. The synthetic data were created using mathematical functions that attempt to emulate the photogrammetric models. Real data were obtained by very low-cost photogrammetric systems specially developed for this experiment. Resulting point clouds were improved when applying the algorithm in synthetic and real experiments, e.g., 25th and 75th error percentiles were reduced from 3.2 cm to 1.4 cm in synthetic tests and from 1.5 cm to 0.5 cm in real conditions.
Note: Reproducció del document publicat a: https://doi.org/10.3390/rs12081240
It is part of: Remote Sensing, 2020, vol. 12, num. 8, p. 1240
URI: http://hdl.handle.net/2445/157998
Related resource: https://doi.org/10.3390/rs12081240
ISSN: 2072-4292
Appears in Collections:Articles publicats en revistes (Dinàmica de la Terra i l'Oceà)

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