We want the least amount of steps users need to take in order to scan for targets.
This is achievable if the target is image-based because Wikitude have cloud recognition.
(By the least amount of steps, I mean, open ar scene and they can start scanning right away.)
With the current object tracking, I don't know how to make this possible.
I understand the technical hurdle of having more than 10+ objects loaded into system memory for tracking. But is there any solution that can scale with object tracking? (Like cloud recognition that can handle a large database of 1000+ image targets)
The problem we're facing is that we need to have more than 10+ objects but WTO can only have a maximum of 10 targets. WTO also has a filesize limitation of 20 MB. Also, switching WTO by pressing buttons or choose from a list is acceptable but we prefer not doing it since it contradicts the UX we have for our app. So I would like to consult for the best alternative first before considering taking those steps.
Unfortunately at the moment the limit is the mentioned 10 objects and the only way to have more objects scannable is like you wrote to e.g. have some form of pre-selection of the .wto file.
Thx and greetings