I believe that fast optimization like in fastPTOptimizer will also be available in Hugin in the next official release.
I see fastPTOptimizer and Hugin++ as a possibility to publish my ideas as sources and also binaries a bit earlier - for encouraging discussions and also because I like using these features for my own panoramas. Maybe there are some features in Hugin++ that shall not be integrated into Hugin for some reasons, e.g. there was a discussion whether weights for control points make sense. Anyway I try to avoid unnecessary changes to the source code in order to facilitate a possible integration of my new features into Hugin. Florian Tobias schrieb am Montag, 28. Juni 2021 um 17:19:18 UTC+2: > 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. >> > -- A list of frequently asked questions is available at: http://wiki.panotools.org/Hugin_FAQ --- You received this message because you are subscribed to the Google Groups "hugin and other free panoramic software" group. To unsubscribe from this group and stop receiving emails from it, send an email to hugin-ptx+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/hugin-ptx/6b88f8b9-bab8-4cab-a574-d3e034530cbfn%40googlegroups.com.
