1,748
Views
8
CrossRef citations to date
0
Altmetric
Research Articles

Exploring the vertical dimension of street view image based on deep learning: a case study on lowest floor elevation estimation

, , ORCID Icon, , & ORCID Icon
Pages 1317-1342 | Received 15 Mar 2021, Accepted 13 Sep 2021, Published online: 06 Oct 2021

References

  • 2018 international building code. 2018. International Code Council, INC.
  • Agarwal, P., Burgard, W., and Spinello, L, 2015. Metric Localization Using Google Street View. In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg Germany, 3111–3118. 10.1109/IROS.2015.7353807
  • Balado, J., et al., 2020. Novel approach to automatic traffic sign inventory based on mobile mapping system data and deep learning. Remote Sensing, 12 (3), 442. doi:10.3390/rs12030442
  • Branson, S., et al., 2018. From google maps to a fine-grained catalog of street trees. ISPRS Journal of Photogrammetry and Remote Sensing, 135 (January), 13–30. doi:10.1016/j.isprsjprs.2017.11.008
  • Bruno, N. and Roncella, R., 2019. Accuracy assessment of 3D models generated from google street view imagery. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-2/W9 (January), 181–188. doi:10.5194/isprs-archives-XLII-2-W9-181-2019
  • Campbell, A., Both, A., and (Chayn) Sun, Q., 2019. Detecting and mapping traffic signs from google street view images using deep learning and GIS. Computers, Environment and Urban Systems, 77 (September), 101350. doi:10.1016/j.compenvurbsys.2019.101350
  • Cavallo, M., 2015. 3D city reconstruction from google street view, https://evl.uic.edu/documents/3drecomstrictionmcavallo.pdf. Accessed 30 January 2021
  • Cawood, T.J., 2005. Evaluating survey methods for obtaining first floor structure elevations for use in federal shore protection studies. Solutions to Coastal Disasters, 2005, 386–394.
  • FEMA, 2010. Home Builder’s guide to coastal construction: technical fact sheet series. Federal Emergency Management Agency, https://campbellriver.ca/docs/default-source/planning-building-development/fema_buildersguide_coastalconstruction.pdf. Accessed 30 January 2021
  • FEMA, 2021. National Flood Insurance Program Flood Insurance Manual. Federal Emergency Management Agency, https://www.fema.gov/sites/default/files/2020-09/fema_flood-insurance-manual-full-edition_april-oct2020.pdf. Accessed 30 January 2021
  • Ghilani, C.D., 2017. Adjustment computations: spatial data analysis. 6th. John Wiley & Sons, Inc., John Wiley & Sons, Inc., Hoboken, New Jersey
  • Gordon, A. and Benjamin, M., 2019. Developing first floor elevation data for coastal resilience planning in Hampton Roads. Hampton Roads Planning District Commission. Chesapeake, Virginia
  • Hara, K., Le, V., and Froehlich, J., 2013. Combining crowdsourcing and google street view to identify street-level accessibility problems. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Paris France, 631–640
  • He, K., et al, 2017. Mask R-CNN. In 2017 IEEE International Conference on Computer Vision (ICCV), Venice Italy, 2980–2988. 10.1109/ICCV.2017.322
  • Hebbalaguppe, R., et al, 2017. Telecom inventory management via object recognition and localisation on google street view images. In 2017 IEEE Winter Conference on Applications of Computer Vision (WACV). Santa Rosa, US. 725–733. 10.1109/WACV.2017.86
  • Ibrahim, S. and Lichti, D., 2012. Curb-based street floor extraction from mobile terrestrial LiDAR point cloud. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 39, B5.
  • Kang, Y., et al., 2020. A review of urban physical environment sensing using street view imagery in public health studies. Annals of GIS, 26 (3), 261–275. doi:10.1080/19475683.2020.1791954
  • Klingner, B., Martin, D., and Roseborough, J, 2013. Street view motion-from-structure-from-motion. In Proceedings of the IEEE International Conference on Computer Vision. Sydney, AU. 953–960
  • Koo, B.W., Guhathakurta, S., and Botchwey, N., 2021 May. How are neighborhood and street-level walkability factors associated with walking behaviors? A big data approach using street view images. Environment and Behavior, 00139165211014609. doi: 10.1177/00139165211014609.
  • Krylov, V.A., Kenny, E., and Dahyot, R., 2018. Automatic discovery and geotagging of objects from street view imagery. Remote Sensing, 10 (5), 661. doi:10.3390/rs10050661
  • Laga, H., et al., 2020. A survey on deep learning techniques for stereo-based depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1. doi:10.1109/TPAMI.2020.3032602
  • Laumer, D., et al., 2020. Geocoding of trees from street addresses and street-level images. ISPRS Journal of Photogrammetry and Remote Sensing, 162 (April), 125–136. doi:10.1016/j.isprsjprs.2020.02.001
  • Liu, L., et al., 2020. Deep learning for generic object detection: A survey. International Journal of Computer Vision, 128 (2), 261–318. doi:10.1007/s11263-019-01247-4
  • Lumnitz, S., et al., 2021. Mapping trees along urban street networks with deep learning and street-level imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 175 (May), 144–157. doi:10.1016/j.isprsjprs.2021.01.016
  • Micusik, B. and Kosecka, J, 2009. “Piecewise planar city 3D modeling from street view panoramic sequences.” In 2009 IEEE Conference on Computer Vision and Pattern Recognition. Miami, US. 2906–2912. 10.1109/CVPR.2009.5206535
  • Ming, Y., et al., 2021. Deep learning for monocular depth estimation: a review. Neurocomputing, 438 (May), 14–33. doi:10.1016/j.neucom.2020.12.089
  • Mooney, S.J., et al., 2016. Use of google street view to assess environmental contributions to pedestrian injury. American Journal of Public Health, 106 (3), 462–469. doi:10.2105/AJPH.2015.302978
  • Needham, H. and Nick, M., 2018. Analyzing the vulnerability of buildings to coastal flooding in Galveston, Texas.
  • Ning, H., et al., 2021. Sidewalk extraction using aerial and street view images. Environment and Planning B: Urban Analytics and City Science. doi:10.1177/2399808321995817
  • Odgers, C.L., et al., 2012. Systematic social observation of children’s neighborhoods using google street view: a reliable and cost-effective method. Journal of Child Psychology and Psychiatry, 53 (10), 1009–1017. doi:10.1111/j.1469-7610.2012.02565.x
  • Redmon, J., et al, 2015. You only look once: unified, real-time object detection. ArXiv:1506.02640 [Cs], June. http://arxiv.org/abs/1506.02640 . Accessed 30 January 2021
  • Redmon, J. and Farhadi, A, 2016. YOLO9000: better, faster, stronger. ArXiv:1612.08242 [Cs], December. http://arxiv.org/abs/1612.08242 . Accessed 30 January 2021
  • Redmon, J. and Farhadi, A. 2018. “YOLOv3: an incremental improvement.” ArXiv:1804.02767 [Cs], April. http://arxiv.org/abs/1804.02767 . Accessed January 30, 2021
  • Schonberger, J.L. and Frahm, J.-M, 2016. Structure-from-motion revisited. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas, US. 4104–4113
  • Taghinezhad, A., et al., 2020. An imputation of first-floor elevation data for the avoided loss analysis of flood-mitigated single-family homes in Louisiana, United States. Frontiers in Built Environment, 6. doi:10.3389/fbuil.2020.00138
  • Tsai, V.J.D. and Chang, C., 2013. Three-dimensional positioning from google street view panoramas. IET Image Processing, 7 (3), 229–239. doi:10.1049/iet-ipr.2012.0323
  • Yan, W.Y., Shaker, A., and Easa, S., 2013. Potential accuracy of traffic signs’ positions extracted from google street view. IEEE Transactions on Intelligent Transportation Systems, 14 (2), 1011–1016. doi:10.1109/TITS.2012.2234119
  • Zhao, Z.-Q., et al., 2019. Object detection with deep learning: a review. IEEE Transactions on Neural Networks and Learning Systems, 30 (11), 3212–3232. doi:10.1109/TNNLS.2018.2876865

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.