This note presents the experimental results deriving from the application of two innovative photogrammetric techniques (with particular reference to non-conventional photogrammetric applications) for the production of time-space 3D models of the marinesurface. Moreover, the first method (automatic three images processing (ATIP)) proposes some easy procedures to solve typicalnon-linear problems of analytical photogrammetry. In particular, once validated the technique of orientation of two images (two-step procedure based on two phases: relative orientation and absolute orientation, both characterized by non-linear functions), wepropose a procedure for the automatic orientation of three images (the introduction of a third image allows avoiding humandecision to find the final solution). The second method (Computer Vision Raspberry Pi—CVR) refers to the use of the Bprompt^technique of computer vision (structure from motion) using five appropriately synchronized cameras to acquire simultaneouslythe various frames, thanks to the use of an acquisition system based on the use of Raspberry Pi. The experimentation wasconducted both in the laboratory (on a model that allows to study a typical phenomenon of the Alpine Valtellina region, in theNorth of Italy) that directly at sea (on a portion of marine surface located in Reggio Calabria near the seafront). The resultsobtained show a substantial comparability of the results both between the two methods and with the actual data measured at seawith dedicated instrumentation.

Innovative techniques of photogrammetry for 3D modeling

BARRILE, Vincenzo;Fotia A
2019-01-01

Abstract

This note presents the experimental results deriving from the application of two innovative photogrammetric techniques (with particular reference to non-conventional photogrammetric applications) for the production of time-space 3D models of the marinesurface. Moreover, the first method (automatic three images processing (ATIP)) proposes some easy procedures to solve typicalnon-linear problems of analytical photogrammetry. In particular, once validated the technique of orientation of two images (two-step procedure based on two phases: relative orientation and absolute orientation, both characterized by non-linear functions), wepropose a procedure for the automatic orientation of three images (the introduction of a third image allows avoiding humandecision to find the final solution). The second method (Computer Vision Raspberry Pi—CVR) refers to the use of the Bprompt^technique of computer vision (structure from motion) using five appropriately synchronized cameras to acquire simultaneouslythe various frames, thanks to the use of an acquisition system based on the use of Raspberry Pi. The experimentation wasconducted both in the laboratory (on a model that allows to study a typical phenomenon of the Alpine Valtellina region, in theNorth of Italy) that directly at sea (on a portion of marine surface located in Reggio Calabria near the seafront). The resultsobtained show a substantial comparability of the results both between the two methods and with the actual data measured at seawith dedicated instrumentation.
2019
Analytical photogrammetry ; Relative orientation; Absolute orientation; Non-linear problems ; Computer vision
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/3280
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