Hello,

what is the reason, that fastPTOptimizer is not part of the official hugin.

Regards,
Tobias

Florian Königstein schrieb am Montag, 28. Juni 2021 um 09:31:08 UTC+2:

> Hugin++ is a fork of Hugin that is linked to fastPTOptimizer, a fork of 
> the libpano13 library.
>
> When you have only a small or medium number of images and control points, 
> the original optimizer does the optimization in a fairly short time. 
> However if you have a large number of images (several hundrets or even more 
> than thousand) and many control points, the original optimizer typically 
> needs much time for the optimization of the parameters.
>
> With Hugin++ the time for the geometrical optimization is much shorter for 
> large panoramas. Speedup factors of 100 or more are possible.
>
> Update 28.06.2021:
>
> I have added support for weights for control points. The default weight 
> for each control points is 1. Assigning a weight higher than 1, say 'w', to 
> a control point is equivalent to have 'w' control points with weight 1 at 
> the same position. This causes the control point's error to contribute 'w' 
> times more to the (weighted) sum of squares that the optimizer tries to 
> minimize.
>
> A control point with a high weight tends to have a small error after 
> optimization - if this is
> possible. But high weights should be used with care: In the extreme case 
> that all control points have a weight of e.g. 1000 the optimizer finds 
> exactly the same parameters as if the control points had the weight 1. What 
> counts is the relation of the weights for the different control points.
>
> What makes sense is assigning higher weights to control points that are 
> likely placed precisely and lower weights to points that are less precise, 
> e.g. if the object where they are placed may have moved in the meantime 
> between shooting the two images.
> You may also assign high weights to control points on objects where larger 
> errors would be visually striking - if you are sure that these objects have 
> not moved much.
>
> For example, I have shot photos for a panorama where are trees, a stream 
> and a bridge over the stream. After optimization without weights for 
> control points (or all CPs having equal weight) there were visually 
> striking errors on the bridge. On the other hand I know that the bridge has 
> not moved noticeably.
> So I could assign higher weights to CPs on the bridge. Other CPs, e.g. on 
> the trees, might have moved - especially if they are on leafs of smaller 
> branches of trees. Of course I tried not to place CPs on leafs but instead 
> on trunks or bigger branches of the trees. But this in not always possible 
> - especially if you use a high focal length (low angle of view).
>
> Generally, assigning higher weight to a control point can lead to smaller 
> errors of the CPs - if this it possible. But this is on the cost of getting 
> larger errors on other control points.
> If the CP with a higher weight is placed precisely, the increase of errors 
> on other control points will probably be tolerable. A counterexample is the 
> following: If a "bad" control point, e.g. an outlier (placed on different 
> objects) or on a moving object, is assigned a higher weight, the error for 
> this CP might decrease, but all other errors might increase in a 
> non-tolerable way.
>
> The "weights for control points" feature is currently available in a 
> development version of Hugin++:
> https://sourceforge.net/projects/huginplusplus/files/development/
>
> Currently the only way to assign weights other than 1 to control points is 
> changing the weight manually in the "control points" tab of Hugin++.  
> Control points that are generated automatically, e.g. by CPfind, will 
> currently have weight 1.
> A nice task for the future would be to change CPfind so that the control 
> points get a weight other than 1 automatically. Some algorithm - including 
> machine learning algorithms - might predict whether the control points 
> might be on a moving object and how large a possible movement might be. 
> With this information the CP detector could assign reasonable weights to 
> the control point.
>

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