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Crowdsourcing Pointclouds:
Trends and Technologies
Digital Image Processing (TKD3606)
Dany Laksono | Dept. of Geodetic
Engineering Universitas Gadjah
Mada
10 March 2020
Crowdsourcing Pointclouds: Trends and Techs
• Crowdsourcing
• Review of Structure from Motion
• Reconstructing in the cloud
• Mapillary, the crowdsourcing platform
Crowdsourcing Spatial Data
Harnessing the power of the crowd to collect geospatial data
VGI (Volunteereed
Geographic Information)
Citizen Journalism
Crowdsourcing Spatial Data
Openstreetmap =
crowdmapping
And it's super effective!
http://www.cs.cornell.edu/~snavely/bundler/
Structure from Motion
SfM: A method to estimate 3D structure as well as position and orientation
of a scene from pairs of images
Structure from Motion
http://www.cs.cornell.edu/projects/bigsfm/
http://www.cs.cornell.edu/projects/1dsfm/
Internet Photos (Flickr, Google
Images, etc):
- No camera parameters
- No initial positions
- Great distortions
- Lots of cameras included
- Selfies!
Crowdsourcing Pointclouds: Is it possible?
CloudSfM
github.com/danylaksono/cloudsfm
Start
User Interface: Login
Frontend Processing
(upload)
Image
validation
Upload image
Backend Processing
(save image)
Image matching
(OpenMVG)
Calc. Camera Matrix
(OpenMVG)
SfM (OpenMVG)
Dense reconstruction
(MVE)
Surface reconstruction
(FSSR)
Texturing (MVST)
Finish
Web Route
SfM Processing
Frontend Download
CloudSfM Algorithm
WebODM
github.com//OpenDroneMap/WebODM
Mapillary: Crowdsourcing Pointclouds
Mapillary Demo!
What Next?
Reconstucting historical camera position
TERIMA KASIH

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Crowdsourcing pointclouds trends and technologies