I scanned a lot of locations and had problems with big-size buildings. Because the Wayspot mobile app scans only 5 meters in height maximum. And if users start to recognize it, they need to stay near the wall and not see a whole building.
Do you have any examples or tricks with big-size scanning and recognizing?
Only way i’d imagine resolving this is by scanning a wayspot across the street or a bit away from the building so you’d know the exact relative pose to the large object. Otherwise overlaying a screenshot that users have to align manually could work and with semantic segmentation cut out the building from the sky. We’ve been looking into this ourselves too but haven’t found a perfect solution yet.
Unfortunately, at the moment, there is no official way to scan large objects or buildings nor would we be able to provide any tips on how it can be accomplished. May I know your use case/ what you’re trying to achieve?
As the documentation suggests, you might be able to do just a face of the building but you won’t be able to do all of it, just what you can capture at a 5 foot distance, but we can’t guarantee that it will work properly since the object being scanned is too large. You can also have a look at our Scanning Best Practices for more information.
@Jesus_Hernandez Similar to the question above, the use case is something like we want to place say Humpty Dumpty on a wall and then on Castle tower which are over 10 metres easily! I see in other threads that it is a bit difficult on the Wayfarer app to do so given the time constraint as well as the capability of phones, so I was wondering if there is a way we could blend/enhance an external 3D mesh generated from a professional lidar/photogrammetry scan and localize it (into a specific location/coordinates) as a wayspot anchor? Basically my idea is to import an external 3D scan into a somewhat crude scan of a building from the Wayfarer app and enrich/super-impose. Hope my query makes sense as this is a make/break deal for us to go the lightship way or the traditional approach.