2025-02-26 How to contribute to Mapillary @ PoliMI

© mapconcierge, CC BY-SA 4.0

20250226 Mapillary Seminar @ PoliMI

Transcript

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8. “Street-level imagery”
9. Maps Satellite / 
 Aerial photos DEM/DSM 3D Models 3D PointClouds Street-level Imagery Non-optical sensors
10. Maps Satellite / 
 Aerial photos DEM/DSM 3D Models 3D PointClouds Street-level Imagery Non-optical sensors
11. What is the most famous street-level imagery service in the world?
13. https://about.google/brand-resource-center/products-and-services/geo-guidelines/#street-view
14. https://about.google/brand-resource-center/products-and-services/geo-guidelines/#street-view
15. https://about.google/brand-resource-center/products-and-services/geo-guidelines/#street-view
16. https://about.google/brand-resource-center/products-and-services/geo-guidelines/#street-view We cannot use Google StreetView data for our research!
18. Yes, We can!
19. If you don’t have Mapillary account, Let’s sign in now!
21. https://www.mapillary.com/mobile-apps
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25. https://www.mapillary.com/app/?lat=35.56668611111112&lng=139.40266666666668&z=17&menu=false&pKey=rPaB0BhwRTpy_7Z6k31oBw&focus=photo&x=0.5097002855874749&y=0.3226481104316623&zoom=0
26. https://www.mapillary.com/app/?pKey=H8wioIgoZFucPG2B9un4zg&focus=photo&lat=34.772989&lng=138.015962&z=17
28. 2.0B Num. of Street-level imageries. https://www.mapillary.com ( 2025/2/5 )
29. https://www.mapillary.com/app/
31. Generating 3D PointCloud by Photogrametory and NeRF method
32. http://blog.mapillary.com/update/2016/09/27/mapillary-joins-berkeley-deepdrive.html
34. Detecting objects by Machine Learning
35. http://blog.mapillary.com/update/2016/09/27/mapillary-joins-berkeley-deepdrive.html
40. 150 object detection classes
41. https://www.mapillary.com/developer/api-documentation/detections
42. Do you know who is the No.1 Mapillary contributor in Italy?
47. I have published 16.1K 360 panoramic photos in the past week, Italy.
51. I have published 57.6K 360 panoramic photos in the past week, Italy.
55. in Milano
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72. # Built-in GPS
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76. # GPS Time correction
77. ※Time Adjuster via GNSS Plugin # GPS Time correction
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80. # Replaceable Battery
83. # USB power supply available
84. # USB power supply available ※No need to open the lid like a GoPro
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89. zenith directly below
90. Bashar Alsadik, 2018. Active use of panoramic mobile mapping systems for as built surveying and heritage documentation 
 https://www.researchgate.net/publication/323206937_Active_use_of_panoramic_mobile_mapping_systems_for_as_built_surveying_and_heritage_documentation directly below zenith zenith directly below
92. 11,008 px 5,504 px
93. 11,008 px 5,504 px 11K Resolution: = 60 GigaPixels
95. # Real-time automatic zenith correction
100. # SD card and internal memory(46GB)
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104. # Handheld style with monopod
105. # Handheld style with monopod ˞1SFGFS
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107. Max: 3m
109. # Shooting is in video mode
110. # Shooting is in video mode ※ 8K/2FPS mp4 + CAMM metadata ※ Maximum Recording Time: 25min
112. # Mapillary Uploader
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116. # Mapillary Tools
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118. mapillary_tools process_and_upload *.mp4
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128. GoPro MAX is cheaper
129. # Embarrassing e-Compass Calibration
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135. https://github.com/gisgeolab/mapillary4milano
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147. # Future
148. # Future * More high Resolution over Giga/Peta Pixel 
 * Realtime Capturing and Publishing 
 * High-precision object recognition * High-precision 3D Scanning 
 * Connecting Metaverse Platform
149. Maps Satellite / 
 Aerial photos DEM/DSM 3D Models 3D PointClouds Street-level Imagery Non-optical sensors
150. How to bring own large geospatial data set?
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154. UNVT Portable Municipality Officer Web browser Orthomosaic Imageries Raster Tile Combined Raster/Vector Tile data set Local Wi-Fi
155. UNVT Portable Municipality Officer Web browser Orthomosaic Imageries Raster Tile Combined Raster/Vector Tile data set Local Wi-Fi
156. BYOG 
 Bring Your Own Geospatial data
158. @mapconcierge