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Marker labelling

Once you have recorded a capture session, the first step in post-processing is to label the recorded markers.
OK. So the first step for postprocessing would normally be to label the markers. So we just took a recording of Mari doing some sort of interpretive dance, which we have displayed here. And what you can see here are the markers that were captured on her body. So we have three head markers– these three– and some markers up and down her arms. You can also see, here, the x, y, and z-axes.
So in this case, the z-axis is the vertical one, and this is determined by the position and the orientation of the ground plane that we set at the time of calibration. This works differently in different motion-capture softwares, but, basically, it’s a good idea to have your participants start off in a very clear and recognisable pose. We often use this T-pose. Are you ready? Yes. –especially if you’re capturing the upper body, so that all of the cameras have a good view on the markers that are up and down the arms. And it’s easy for you when you go to try to figure out which marker corresponds to which body part.
It’s easy for you to see where the markers are, relative to each other. So Mari is labelling this marker. This is the marker that, I believe, is on the front of her head. So she’s assigning it a label now.
And then this would be– I don’t know. What is that, the top of your head? Or– I think it’s right. –right side of the head. She’s assigning a label to this one.
And the process would be just to go through all of your markers and assign labels.
And once this is done, the next step would be to look at the quality of the trajectory that you captured during the recording. And, with any luck, the marker was actually visible through most of the recording or all of the recording, and therefore you have a fairly complete trajectory recorded. But if that’s not the case, then there may be gaps in the recorded trajectory.
For example, in this case, that’s the right hand. So you can see that the trajectory only goes partway. So the cameras were able to see this marker until, what, 7,000 milliseconds or something in. And then it disappeared, so it was covered up by something. And so what Mari would have to do now is go to after that marker has disappeared in the timeline.
Can you go back a little? So there it is– the right hand. And then when you go back further– it disappeared. So it got too high and the cameras couldn’t see it anymore. But then it has reappeared again when she brought her arm down, so now she’s able to relabel that marker. So she’s got it to here, where you can still see the label of the right hand. And then when she goes a little bit further, the right hand disappears– you can see that the marker disappears– and then it comes back for a short period– disappears again.
So every time it reappears, you have to relabel it with the same label as before and then all of those trajectories can be joined together.
In this case, this was a short recording. So even though this marker disappeared a few times, it doesn’t take very much time to relabel all the segmented parts of the trajectory. But you can imagine, in a very long recording where you have many markers, if you have a lot of cases of this where markers are disappearing and coming back, then it can take a very long time to go through and fix everything up and label everything properly. So this is why it’s super important to try to get a good capture where your markers are not constantly disappearing or flickering away.
Maybe we can also say a little bit about the trajectory. So usually, in these softwares, you can see the x, y, and z-trajectories of the different markers. So these indicate how the movement was on the three different axes throughout the trial. And it’s good to have a look at these trajectories and see if they make sense because sometimes, you might see kind of weird jumps. So the hand marker is here and then, all of a sudden, it makes a big vertical jump as though the person’s hand jumped in a fraction of a second. And this kind of artefact suggests that there’s a problem with the labelling, so that also needs to be fixed.
So I guess everybody’s got their own way of doing the labelling. [LAUGHTER] And one way to do it is to have the largest sections first, but there is really not one way of doing it. So you can see here, under Fill Level, it tells you the percentage of the trial that each marker is labelled for. So some of them have been labelled now for 100%, which is great. And others are down in the 80s or 90s.
So the ones that do not have 100% labelled means that there’s some gaps in the trajectory.

Once you have recorded a capture session, the first step in post-processing is to label the recorded markers. This involves assigning a meaningful name to each marker. It also involves joining together broken trajectories, which occur as a result of marker drop-out.

In this video, Laura and Mari explain the process of marker labelling. They demonstrate using a motion capture processing software that we have in the lab at RITMO.

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Motion Capture: The Art of Studying Human Activity

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