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Day1-1440-High precision mapping with streetlevel imagery

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September 01, 2017

Day1-1440-High precision mapping with streetlevel imagery

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sotm2017

September 01, 2017
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Transcript

  1. High Precision Mapping with Street-level imagery

  2. Current state of the map:

  3. 116.8million highways Source: Jennings Anderson

  4. Source: Jennings Anderson 28.6% (33million) roads have names

  5. • 28.6% have names • 9.6% are oneways • 6.4%

    have speed-limits • 4.2% have access tags
  6. 242million buildings Source: Jennings Anderson

  7. • 3.6% have building levels • 1.6% have names

  8. 11.6million amenities 47% have names

  9. How do we improve this?

  10. Most common sources for remote mapping:

  11. Satellite and aerial imagery

  12. Third party data

  13. GPS Traces

  14. Street-level imagery

  15. What is Street-level imagery?

  16. Images having: • latitude, longitude • altitude (optionally) • bearing

  17. Most common open-licensed, street-level imagery providers

  18. Editing OpenStreetMap using street-level imagery

  19. has plugins for: • Mapillary • OpenStreetCam

  20. Download plugins: ‘Preferences’ -> ‘Plugins’

  21. Open plugins from ‘Imagery’

  22. None
  23. None
  24. has support for Mapillary

  25. In ‘Map Data’ turn on ‘Photo Overlay’ and ‘Traffic Sign

    Overlay’
  26. None
  27. Mapping common features from street-level imagery

  28. Traffic Signs

  29. detects traffic signs from images

  30. None
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  40. Building Details

  41. None
  42. How we use street-level imagery at Mapbox

  43. Mapping Navigational assets

  44. osm-navigation map: mapbox.github.io/osm-navigation-map/

  45. Verifying user feedbacks

  46. Detecting harmful/incorrect edits

  47. Future Potential

  48. Source: mapbox.github.io/osm-analysis-collab/editor-density Mappers are everywhere

  49. Current Mapillary coverage

  50. Email: oindrila@mapbox.com Twitter: Oindrila_G

  51. Questions?