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UID:pretalx-foss4g-2022-7UAP8S@talks.staging.osgeo.org
DTSTART;TZID=CET:20220825T153000
DTEND;TZID=CET:20220825T153500
DESCRIPTION:Mapping is time-consuming and requires a high volume of a workf
 orce when it comes to keep maps up to date periodically. This brings the n
 eed of finding alternative approaches to keep maps up to date. Mobile mapp
 ing is the process of collecting geospatial data from a mobile vehicle usi
 ng a 360º camera\, laser scanner\, GPS/IMU positioning system\, and other
  sensors. \n\nMany devices now include a geotag for every photo captured\,
  and GPS accuracy can	have major effects on the quality of street-level im
 agery and derived data. Join us in an exploration of the different accurac
 y levels of GPS-enabled cameras\, where we will take a look at how differe
 nt devices compare\, and what varied levels of GPS accuracy look like both
  for image location and for data extracted using computer vision and struc
 ture from motion.\n\nUnderstanding the differences between devices is an i
 mportant step in planning street-level imagery capture\, as it will align 
 your expectations with the advantages and limitations of the hardware you 
 use. We tested various devices and will share the results of our investiga
 tion\, with the aim of equipping you to capture street-level imagery with 
 the tools and methods that fit your needs.
DTSTAMP:20260403T194549Z
LOCATION:Modulo 0
SUMMARY:The most accurate cameras to generate map data from street-level im
 agery - Christopher Beddow\, Said Turksever\, Edoardo Neerhut
URL:https://talks.staging.osgeo.org/foss4g-2022/talk/7UAP8S/
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