![]() “Ultra-Fast Structured Motion”: We are very particularly perceptive to human actions. (of course, sometimes this is what you want).Ĩ. “Specular Highlights”: If you have moving lights, e.g., a shiny object that reflects the light as it moves, it might cause problems because when the motion estimator attempts to match two images, as the motion estimator will tend to follow the highlight as if it was an object. The PRO version manual explains ways to handle such issues.ħ. “Alternate Motions”: When motions going in different direction are layered it is possible that the dominant motion affects (spills into) the background motion. If you leave the duplicate frames (or fields, in the case of 3:2 pulldown) the freeze-frame, inherent in the duplication of the frames, will be stretched (or sped up, as appropriate).Ħ. Also, you should be aware that if your material has 3:2 pulldown you should remove it beforehand. As such, you will need to remove duplicated frames before the application of Twixtor. ![]() “Duplicated Frames”: Twixtor does not provide automatic duplicated frame detection support. Because fields are spatially a line offset from each other, regions where there is no motion and horizontal lines might produce a slight up and down motion in phase with the source frame rate, for that reason some people prefer to first deinterlace their footage with a tool like FieldsKitĥ. Always remember that by definition, even and odd scan lines in material with fields are considered half a frame apart timewise. ![]() “Fields”: We provide some basic field handling. You might try using the Mark Segments feature to mark these single frame defects as a separate clip to avoid the defect from spreading it’s influence into other frames.Ĥ. Also, if there is a piece of hair or a scratch on the scanned film for a frame this would influence the tracking so you really should try to clean such defects before processing. “Short Interval Defects” : Sudden global illumination change (e.g., a flash), strobing, dust, … can create unexpected / undesired results. Some cameras for example will streak under fast motion and that can create disappointing tracking results.ģ. “Transparency”: Overlay of semi-opaque surfaces might create unexpected results. Any very structured pattern rotating can cause “blind spots” for the analyzer.Ģ. the same person hand for instance) might confuse the motion vector calculation. “Picket Fence”: A very regular pattern in motion (for example someone wearing a t-shirt with fine stripes) with an object moving in front of it (e.g. As you become an expert user, you learn to predict the kind of material that can cause problems.ġ. The idea here is not to discourage you and tell you it does not work but, rather, to give truth in advertising. It might happen that Twixtor might do poorly in specific instances. This information will be of more use to you as you become more familiar with Twixtor and want to understand how to generate the best possible results. If you have not used Twixtor yet, this section might prove to be a little bit esoteric. You probably want to read about “problematic footage” from our manual that I reproduce below. Our Pro version allows you to roto the skier (frame by frame animation) and then use that to tell Twixtor that the skier is a separate object to be tracked, but even that takes a bit of trial and error with shooting properly to allow that to work. However, I suspect there’s not much you can do to get the ghosting to disappear (even after watching that tutorial), except to shoot next time using a higher frame rate. You can reduce the “gloopiness” by watching this help tutorial. Ah, if you have a lot of motion (or objects crossing each other with a fair amount of motion) then you will see this problem.
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