Video acquisition with 360° (spherical) cameras is becoming increasingly popular for the opportunity to capture the entire scene around the user in a relatively short time. The method can also be attractive for photogrammetric applications. As the overlap between consecutive frames is undoubtedly guaranteed, 3D models can be generated with an automated processing workflow. The paper illustrates the results achieved with 5k 360° videos captured with different Insta360 cameras. As the number of frames can become large, two complementary solutions are proposed to provide approximate initial exterior orientation parameters: The integration of the trajectory captured through GNSS, and the creation of an acquisition plan with a GIS-based application. The availability of approximated EO parameters provides a visibility map between the frames and reduces the computational cost during image matching. Experimental results demonstrate that such preliminary information is necessary for large datasets. Indeed, the photogrammetric processing of the entire dataset without the proposed preliminary EO parameters resulted in unreliable or incomplete orientation results.

3D MODELING WITH 5K 360° VIDEOS

Barazzetti L.;Previtali M.;Roncoroni F.
2022-01-01

Abstract

Video acquisition with 360° (spherical) cameras is becoming increasingly popular for the opportunity to capture the entire scene around the user in a relatively short time. The method can also be attractive for photogrammetric applications. As the overlap between consecutive frames is undoubtedly guaranteed, 3D models can be generated with an automated processing workflow. The paper illustrates the results achieved with 5k 360° videos captured with different Insta360 cameras. As the number of frames can become large, two complementary solutions are proposed to provide approximate initial exterior orientation parameters: The integration of the trajectory captured through GNSS, and the creation of an acquisition plan with a GIS-based application. The availability of approximated EO parameters provides a visibility map between the frames and reduces the computational cost during image matching. Experimental results demonstrate that such preliminary information is necessary for large datasets. Indeed, the photogrammetric processing of the entire dataset without the proposed preliminary EO parameters resulted in unreliable or incomplete orientation results.
2022
9TH INTERNATIONAL WORKSHOP 3D-ARCH 3D VIRTUAL RECONSTRUCTION AND VISUALIZATION OF COMPLEX ARCHITECTURES, VOL. 46-2
360°
5k
Accuracy
Automation
Low-cost sensor
Orientation
Video
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1214437
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