Back to the future: il ritorno della Fotogrammetria

Fabio Remondino, Daniela Poli


The 3D reconstruction of scenes and objects at different scales is generally performed today using range or image data. For more than a decade, range sensors have been growing in popularity as a fundamental source of dense point clouds for 3D documentation, mapping and visualization
purposes at various scales. Over the same period, and until quite recently, photogrammetry was not able to efficiently deliver dense and detailed 3D point clouds similar to those produced by ranging instruments. Consequently range sensors became the dominant technology for dense 3D recording, replacing photogrammetry in many application areas. Thanks to recent significant improvements in hardware (such as better dynamics and radiometry) and algorithms (for
example Structure from Motion (SfM) or innovative image matching algorithms), photogrammetry has re-emerged as a competitive technology and a resurgence of automated photogrammetric methods is now evident. Therefore the market, which was previously primarily dominated by
airborne and terrestrial range sensors, nowadays offers more image-based measurement tools for 3D recording and modelling.

Parole chiave

Fotogrammetria; image based; dense image matching; nuvole di punti 3d; droni; laser scanner

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Riferimenti bibliografici

GRUEN, A., 2012. Development and status of image matching in photogrammetry. Photogrammetric Record, 27(137), 36-57.

HIRSCHMUELLER, H., 2008. Stereo processing by semi-global matching and mutual information.

IEEE Transactions on Pattern Analysis and Machine

Intelligence, 30(2): 328-341.

REMONDINO, F., DEL PIZZO, S., KERSTEN, T., TROISI, S., 2012. Low-cost and open-source solutions for automated image orientation – A critical overview. Lecture Notes in Computer Science, 7616: 40-54

REMONDINO, F., SPERA, M.G., NOCERINO, E., MENNA, F., NEX, F., 2014. State of the art in high density image matching. Photogrammetric Record, in press.

REMONDINO, F., RUPNIK, E., NEX, F., 2014. Automated processing of oblique imagery. GIM International, Vol. 28(2): 16-19.



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