3D mapping is becoming increasingly popular for their applications in industrial, disaster management, and healthcare. Thus, 3D mapping techniques for different data sources are urgently needed. In this study, the proposed technique is based on the spherical images because its 720-degree field-of-view and its sequential data acquisition are friendly to the user. 3D Mapping generation is performed in three stages. The first stage that has to be done toward the setting-up of the reconstruction tool is the acquisition of a valid data set. In particular, our case study considers the point cloud of the Department of Geomatics of a university building in the city campus of Tainan, which is thought to be a suitable example for the experiments. After an acquisition, the second stage is to import the stitched spherical images into Agisoft Photoscan Pro for 3D modeling. The photo triangulation is conducted by Structure-from-Motion (SfM) technique and the positioning accuracy was assessed within the Photoscan Pro software. Later, a dense point cloud can be produced. The third stage is to import the produced dense point cloud into Revit software for generating 3D building CAD model. In order to evaluate accuracy, we have compared indoor and outdoor environment with each one featuring a diverse number of images, varying GSDs (Ground Sample Distances), and some reference information to perform metric analyses of the results, e.g. reference lines measured with a roll meter and reference points as measured by a total station. In this research, we have compared angle delineation within Revit software. The images were acquired by the Garmin VIRB 360 and Samsung Gear 360. For an overall accuracy assessment, the Garmin VIRB 360 performs better than Samsung Gear 360. The spherical images are very simple for a large environment, rapid data acquisition and easy to realize, they are low cost for human resource and time, and they are a very useful and powerful tool for the documentation and survey of the building.

Agarwal, S. (2010). Bundle Adjustment in the Large Sameer. Proc. European Conference on Computer Vision, 29–42. https://doi.org/10.1007/978-3-642-15552-9_3
Alsadik, B. S. A. (2014). Guided close range photogrammetry for 3D modelling of cultural heritage sites. https://doi.org/10.3990/1.9789036537933
An, Z. (2017). Accuracy Assessment of 3D Point Clouds Generated by Photogrammetry From Different Distances.
Barazzetti, L., Previtali, M., & Roncoroni, F. (2017). 3D modelling with the samsung gear 360. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 42(2W3), 85–90. https://doi.org/10.5194/isprs-archives-XLII-2-W3-85-2017
Cohen, A., Schönberger, J. L., Speciale, P., Sattler, T., Frahm, J. M., & Pollefeys, M. (2016). Indoor-outdoor 3D reconstruction alignment. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9907 LNCS, 285–300. https://doi.org/10.1007/978-3-319-46487-9_18
Crandall, D. J., Owens, A., Snavely, N., & Huttenlocher, D. P. (2013). SfM with MRFs: Discrete-continuous optimization for large-scale structure from motion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(12), 2841–2853. https://doi.org/10.1109/TPAMI.2012.218
Deakin, R. E., & Kildea, D. G. (1999). A note on standard deviation and RMS. Australian Surveyor, 44(1), 74–79. https://doi.org/10.1080/00050351.1999.10558776
Fangi, G. (2006). Investigation on the suitability of the spherical panoramas by Realviz Stitcher for metric purposes. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36(5), 372–376.
Fangi, G. (2007). The Multi-image spherical Panoramas as a tool for Architectural Survey. XXI International CIPA Symposium, (October), 0256--1840. https://doi.org/10.1093/jpe/rtt066
Garmin Ltd. (2017). User Guide on GARMIN VIRB 360.
Gottardi, C., & Guerra, F. (2018). Spherical images for cultural heritage: Survey and documentation with the NIKON KM360. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 42(2), 385–390. https://doi.org/10.5194/isprs-archives-XLII-2-385-2018
Granshaw, S. I. (2016). Photogrammetric Terminology: Third Edition. Photogrammetric Record, 31(154), 210–252. https://doi.org/10.1111/phor.12146
Guan, X. (2011). Spherical Image Processing for Immersive Visualisation and View Generation, (November).
Im, S., Ha, H., Choe, G., Jeon, H. G., Joo, K., & Kweon, I. S. (2015). High quality structure from small motion for rolling shutter cameras. Proceedings of the IEEE International Conference on Computer Vision, 2015 Inter, 837–845. https://doi.org/10.1109/ICCV.2015.102
Kwiatek, K., & Tokarczyk, R. (2014). Photogrammetric Applications of Immersive Video Cameras. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, II-5(June), 211–218. https://doi.org/10.5194/isprsannals-II-5-211-2014
Kwiatek, K., & Tokarczyk, R. (2015). Immersive photogrammetry in 3D modelling. Geomatics and Environmental Engineering, 9(2), 51. https://doi.org/10.7494/geom.2015.9.2.51
Luhmann, T., Kyle, S., & Boehm, J. (2014). Close-Range Photogrammetry and 3D Imaging. De Gruyter, 2nd editio.
Luhmann, T., & Tecklenburg, W. (2004). 3-D Object Reconstruction From Multiple-Station Panorama Imagery. Institute for Applied Photogrammetry and Geoinformatics, 1–8.
Macher, H., Landes, T., & Grussenmeyer, P. (2017). From Point Clouds to Building Information Models: 3D Semi-Automatic Reconstruction of Indoors of Existing Buildings. Applied Sciences, 7(10), 1030. https://doi.org/10.3390/app7101030
Menna, F., Nocerino, E., Remondino, F., Dellepiane, M., Callieri, M., & Scopigno, R. (2016). 3D Digitization of an heritage masterpiece - A critical analysis on quality assessment. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 41(July), 675–683. https://doi.org/10.5194/isprsarchives-XLI-B5-675-2016
Nocerino, E., Menna, F., & Remondino, F. (2014). Accuracy of typical photogrammetric networks in cultural heritage 3D modeling projects. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 40(5), 465–472. https://doi.org/10.5194/isprsarchives-XL-5-465-2014
Pagani, A., Gava, C., Cui, Y., Krolla, B., Hengen, J.-M., & Stricker, D. (2011). Dense 3D Point Cloud Generation from Multiple High-resolution Spherical Images. … Symposium on Virtual …, 17–24. https://doi.org/10.2312/VAST/VAST11/017-024
Perfetti, L. (2018). Fisheye Photogrammetry to Survey Narrow Spaces in Architecture and a Hypogea Environment, 3–28.
Previtali, M., Barazzetti, L., Brumana, R., & Scaioni, M. (2014). Towards automatic indoor reconstruction of cluttered building rooms from point clouds. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2(5), 281–288. https://doi.org/10.5194/isprsannals-II-5-281-2014
Ramos, A. P., & Prieto, G. R. (2016). Only image based for the 3D metric survey of gothic structures by using frame cameras and panoramic cameras. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 41(July), 363–370. https://doi.org/10.5194/isprsarchives-XLI-B5-363-2016
Remondino, F., Nocerino, E., Toschi, I., & Menna, F. (2017). A critical review of automated photogrammetric processing of large datasets. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 42(2W5), 591–599. https://doi.org/10.5194/isprs-archives-XLII-2-W5-591-2017
Rothermel, M., Wenzel, K., Fritsch, D., & Haala, N. (2012). SURE - Photogrammetric surface reconstruction from imagery. LC3D Workshop, 1–9.
Samsung Electronics. (2017). User Guide on Samsung Gear 360, 1, 1–53.
Schonberger, J. L., & Frahm, J.-M. (2016). Structure-From-Motion Revisited. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/CVPR.2016.445
Strecha, C., & Glassey, L. (2015). Terrestrial 3D Mapping Using Fisheye, (February).
Sunghoon Im, Hyowon Ha, Hae-Gon Jeon, G. C. and I. S. K. (2016). All-around Depth from Small Motion with A Spherical Panoramic Camera. Springer International Publishing AG, (3), 156–172. https://doi.org/10.1007/978-3-319-46487-9
Tang, P., Huber, D., Akinci, B., Lipman, R., & Lytle, A. (2010). Automatic reconstruction of as-built building information models from laser-scanned point clouds: A review of related techniques. Automation in Construction, 19(7), 829–843. https://doi.org/10.1016/j.autcon.2010.06.007
Ullman, S. (2018). The Interpretation of Structure from Motion Author ( s ): S . Ullman Source : Proceedings of the Royal Society of London . Series B , Biological Sciences , Vol . 203 , Published by : Royal Society Stable URL : https://www.jstor.org/stable/77505, 203(1153), 405–426.
Wang, X., Wu, K., & Wang, S. (2013). Research on Panoramic Image Registration Approach based on Spherical Model, 6(6), 297–308.
Wolf, P. R., & Dewitt, B. A. (2000). Elements Of Photogrammetry With Applications in GIs. Thomas Casson.