Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 681-687, 2016
https://doi.org/10.5194/isprs-archives-XLI-B1-681-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
06 Jun 2016
PHOTOGRAMMETRIC RECONSTRUCTION WITH BAYESIAN INFORMATION
A. Masiero, F. Fissore, A. Guarnieri, F. Pirotti, and A. Vettore Interdepartmental Research Center of Geomatics (CIRGEO), University of Padova, Viale dell’Universit`a 16, Legnaro (PD) 35020, Italy
Keywords: 3D reconstruction, Structure from Motion, Feature matching, Inertial Sensors, UWB Abstract. Nowadays photogrammetry and laser scanning methods are the most wide spread surveying techniques. Laser scanning methods usually allow to obtain more accurate results with respect to photogrammetry, but their use have some issues, e.g. related to the high cost of the instrumentation and the typical need of high qualified personnel to acquire experimental data on the field. Differently, photogrammetric reconstruction can be achieved by means of low cost devices and by persons without specific training. Furthermore, the recent diffusion of smart devices (e.g. smartphones) embedded with imaging and positioning sensors (i.e. standard camera, GNSS receiver, inertial measurement unit) is opening the possibility of integrating more information in the photogrammetric reconstruction procedure, in order to increase its computational efficiency, its robustness and accuracy. In accordance with the above observations, this paper examines and validates new possibilities for the integration of information provided by the inertial measurement unit (IMU) into the photogrammetric reconstruction procedure, and, to be more specific, into the procedure for solving the feature matching and the bundle adjustment problems.
Conference paper (PDF, 2345 KB)


Citation: Masiero, A., Fissore, F., Guarnieri, A., Pirotti, F., and Vettore, A.: PHOTOGRAMMETRIC RECONSTRUCTION WITH BAYESIAN INFORMATION, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B1, 681-687, https://doi.org/10.5194/isprs-archives-XLI-B1-681-2016, 2016.

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