WEBVTT 00:00:00.000 --> 00:00:05.100 align:middle line:90% 00:00:05.100 --> 00:00:07.140 align:middle line:84% Now we have been looking at different types 00:00:07.140 --> 00:00:10.350 align:middle line:84% of motion capture, where we can put markers on the body 00:00:10.350 --> 00:00:14.850 align:middle line:84% and capture the motion of people with a very high level 00:00:14.850 --> 00:00:16.470 align:middle line:90% of accuracy and precision. 00:00:16.470 --> 00:00:18.420 align:middle line:84% And that's often the preferable way 00:00:18.420 --> 00:00:23.280 align:middle line:84% of doing it when we're doing the type of studies we do. 00:00:23.280 --> 00:00:25.260 align:middle line:84% But I would also like to mention that there 00:00:25.260 --> 00:00:29.190 align:middle line:84% are many also good reasons for doing regular video recordings 00:00:29.190 --> 00:00:32.189 align:middle line:90% and do analysis based on video. 00:00:32.189 --> 00:00:36.090 align:middle line:84% And first of all, one of the nice things about video cameras 00:00:36.090 --> 00:00:38.280 align:middle line:90% is that they are everywhere. 00:00:38.280 --> 00:00:41.830 align:middle line:84% You have them in your mobile phone. 00:00:41.830 --> 00:00:44.460 align:middle line:84% So from this you can actually get a quite nice video 00:00:44.460 --> 00:00:45.630 align:middle line:90% recording. 00:00:45.630 --> 00:00:47.970 align:middle line:84% At least if you put it on a tripod, 00:00:47.970 --> 00:00:51.150 align:middle line:84% so the camera doesn't move very much. 00:00:51.150 --> 00:00:53.530 align:middle line:84% You can also get all sorts of other types of cameras 00:00:53.530 --> 00:00:54.030 align:middle line:90% these days. 00:00:54.030 --> 00:00:56.370 align:middle line:10% For example, such portable action cameras that 00:00:56.370 --> 00:01:00.000 align:middle line:10% are quite nice to put up in different constellations. 00:01:00.000 --> 00:01:02.640 align:middle line:84% I often like to put them in the ceiling above a stage, where 00:01:02.640 --> 00:01:04.920 align:middle line:84% it's possible to look at how performers, for example, 00:01:04.920 --> 00:01:05.940 align:middle line:90% move on stage. 00:01:05.940 --> 00:01:07.950 align:middle line:84% Or you can put them in all the small spots where 00:01:07.950 --> 00:01:10.260 align:middle line:84% it's difficult to get through to be able to look 00:01:10.260 --> 00:01:11.220 align:middle line:90% at what's going on. 00:01:11.220 --> 00:01:14.580 align:middle line:84% For example, like looking at the feet of a pianist. 00:01:14.580 --> 00:01:17.040 align:middle line:84% Of course, you can also scale up and have a more, 00:01:17.040 --> 00:01:18.660 align:middle line:84% kind of a little bit larger camera 00:01:18.660 --> 00:01:21.820 align:middle line:84% that you can put at the front of a stage. 00:01:21.820 --> 00:01:24.850 align:middle line:84% Or even go up to more kind of professional type of cameras, 00:01:24.850 --> 00:01:27.750 align:middle line:84% like this one, if you really want to get good results. 00:01:27.750 --> 00:01:32.280 align:middle line:84% But for many purposes, you can get very good results 00:01:32.280 --> 00:01:35.590 align:middle line:84% out of just using a small little camera. 00:01:35.590 --> 00:01:39.368 align:middle line:84% So when it comes to recording video for analysis, 00:01:39.368 --> 00:01:41.160 align:middle line:84% that's quite different than recording video 00:01:41.160 --> 00:01:43.860 align:middle line:84% for aesthetic reasons or for doing 00:01:43.860 --> 00:01:45.390 align:middle line:90% other types of production. 00:01:45.390 --> 00:01:48.810 align:middle line:84% Because usually then people would move the cameras a lot, 00:01:48.810 --> 00:01:51.360 align:middle line:90% zoom in, pan, tilt, et cetera. 00:01:51.360 --> 00:01:55.170 align:middle line:84% But when you're doing analysis on video material, 00:01:55.170 --> 00:01:56.880 align:middle line:84% that type of movement of the camera 00:01:56.880 --> 00:01:58.860 align:middle line:84% is not very good, because that will show up 00:01:58.860 --> 00:02:01.330 align:middle line:90% in the video analysis. 00:02:01.330 --> 00:02:05.610 align:middle line:10% So when we shoot video for analysis purposes, 00:02:05.610 --> 00:02:10.110 align:middle line:10% we always try to have the camera stand still on the tripod 00:02:10.110 --> 00:02:13.470 align:middle line:10% or on a table or some other kind of stand, 00:02:13.470 --> 00:02:15.090 align:middle line:10% so that it's possible to only capture 00:02:15.090 --> 00:02:18.480 align:middle line:10% the motion within the frame and not the movement of the camera 00:02:18.480 --> 00:02:19.290 align:middle line:10% itself. 00:02:19.290 --> 00:02:22.050 align:middle line:84% We also try to have, then, good light 00:02:22.050 --> 00:02:24.480 align:middle line:84% and also try to remove the background as much 00:02:24.480 --> 00:02:26.430 align:middle line:84% as possible so that it's easy to look 00:02:26.430 --> 00:02:27.870 align:middle line:90% at what is in the foreground. 00:02:27.870 --> 00:02:31.800 align:middle line:84% For example, a musician or a dancer on stage. 00:02:31.800 --> 00:02:35.340 align:middle line:84% So then if you have made a recording that you think is 00:02:35.340 --> 00:02:38.310 align:middle line:84% nice and that you want to use for analysis, 00:02:38.310 --> 00:02:41.460 align:middle line:84% then there are different approaches to how to analyse 00:02:41.460 --> 00:02:42.740 align:middle line:90% this. 00:02:42.740 --> 00:02:45.040 align:middle line:84% And one of them is that of doing a more 00:02:45.040 --> 00:02:49.410 align:middle line:84% of a qualitative analysis, which is based on observation. 00:02:49.410 --> 00:02:52.620 align:middle line:84% And in that case, you would take a look at the video file, 00:02:52.620 --> 00:02:55.350 align:middle line:84% and just by your eyes, observe what is going on. 00:02:55.350 --> 00:02:58.230 align:middle line:84% For example, also notate down, or use a computer programme 00:02:58.230 --> 00:03:03.850 align:middle line:84% to help in making a notation of the video in question. 00:03:03.850 --> 00:03:06.960 align:middle line:84% The next step could be to do more of a quantitative type 00:03:06.960 --> 00:03:10.740 align:middle line:84% of analysis, where you run the video through a computer 00:03:10.740 --> 00:03:13.800 align:middle line:84% programme that will calculate different types of features. 00:03:13.800 --> 00:03:15.780 align:middle line:84% And it can calculate, for example, the quantity 00:03:15.780 --> 00:03:21.120 align:middle line:84% of motion, that is, how much a person is moving in the frame. 00:03:21.120 --> 00:03:23.760 align:middle line:84% Look at where in the frame a person is moving. 00:03:23.760 --> 00:03:26.490 align:middle line:84% For example, kind of up and down or sideways. 00:03:26.490 --> 00:03:29.260 align:middle line:90% And other the types of features. 00:03:29.260 --> 00:03:31.530 align:middle line:84% So that's kind of the qualitative and quantitative 00:03:31.530 --> 00:03:33.210 align:middle line:84% type of approaches to video analysis, 00:03:33.210 --> 00:03:34.843 align:middle line:84% but there's also something in between 00:03:34.843 --> 00:03:36.510 align:middle line:84% that we have been working on quite a lot 00:03:36.510 --> 00:03:37.980 align:middle line:90% here at the University of Oslo. 00:03:37.980 --> 00:03:41.050 align:middle line:10% And that is what we call video visualisation. 00:03:41.050 --> 00:03:44.220 align:middle line:10% And this is a way of doing a kind of quantitative type 00:03:44.220 --> 00:03:49.200 align:middle line:10% of analysis on the video, but made for qualitative purposes. 00:03:49.200 --> 00:03:52.920 align:middle line:84% And one such example, here, is what I have behind me here. 00:03:52.920 --> 00:03:55.830 align:middle line:84% And this is what I call a motiongram. 00:03:55.830 --> 00:03:58.560 align:middle line:10% And this is a very compact representation 00:03:58.560 --> 00:04:01.110 align:middle line:10% of a movement sequence. 00:04:01.110 --> 00:04:04.440 align:middle line:84% In this case, it's the movement of a dancer. 00:04:04.440 --> 00:04:07.850 align:middle line:84% And this is the original video file. 00:04:07.850 --> 00:04:13.160 align:middle line:84% So we see here that a dancer, she's moving her arms-- 00:04:13.160 --> 00:04:16.730 align:middle line:84% And this is from a study we did looking at spontaneous dance 00:04:16.730 --> 00:04:18.320 align:middle line:90% movements to music. 00:04:18.320 --> 00:04:20.600 align:middle line:84% And, just by looking at this, we get 00:04:20.600 --> 00:04:26.060 align:middle line:84% a sense of how the movement is unfolding in time and space. 00:04:26.060 --> 00:04:28.760 align:middle line:84% But it's difficult to really grasp 00:04:28.760 --> 00:04:30.390 align:middle line:90% how it looks like over time. 00:04:30.390 --> 00:04:33.510 align:middle line:84% So, for example, if you want to put this into a research paper, 00:04:33.510 --> 00:04:36.930 align:middle line:84% we need to capture this in one way or another. 00:04:36.930 --> 00:04:39.680 align:middle line:84% And that's when these motiongrams are useful. 00:04:39.680 --> 00:04:42.920 align:middle line:84% Because the motiongram is a representation of the movement 00:04:42.920 --> 00:04:43.850 align:middle line:90% we just saw. 00:04:43.850 --> 00:04:47.250 align:middle line:84% We can see the hands, her hands, moving up and down here. 00:04:47.250 --> 00:04:49.670 align:middle line:84% Here she's standing more or less still. 00:04:49.670 --> 00:04:51.990 align:middle line:84% And then here she's moving up again. 00:04:51.990 --> 00:04:55.280 align:middle line:84% So it's kind of a way of representing 00:04:55.280 --> 00:04:58.880 align:middle line:90% the motion over time. 00:04:58.880 --> 00:05:01.130 align:middle line:10% This is just one of many different types 00:05:01.130 --> 00:05:04.070 align:middle line:10% of video visualisations. 00:05:04.070 --> 00:05:07.400 align:middle line:84% One of the reasons it's possible to do any type of analysis 00:05:07.400 --> 00:05:11.240 align:middle line:84% of a video file to start with is that a video file is actually 00:05:11.240 --> 00:05:13.020 align:middle line:90% just a series of numbers. 00:05:13.020 --> 00:05:15.530 align:middle line:84% So it's a kind of a matrix, where 00:05:15.530 --> 00:05:19.130 align:middle line:84% you have the grid, where you have the pixels in the image. 00:05:19.130 --> 00:05:24.140 align:middle line:84% And then you have four layers in each of the frames that will 00:05:24.140 --> 00:05:26.720 align:middle line:84% correspond to the different colours in the image. 00:05:26.720 --> 00:05:29.490 align:middle line:84% So based on these numbers, it's possible to calculate, 00:05:29.490 --> 00:05:31.820 align:middle line:84% for example, the average of what is going 00:05:31.820 --> 00:05:34.460 align:middle line:90% on in one of these images. 00:05:34.460 --> 00:05:36.920 align:middle line:84% And one technique that we often use 00:05:36.920 --> 00:05:41.300 align:middle line:84% is to create what we call a motion image. 00:05:41.300 --> 00:05:44.510 align:middle line:84% And here it is that we will start from a normal video 00:05:44.510 --> 00:05:48.080 align:middle line:84% recording, then we can crop it a little bit so that you get 00:05:48.080 --> 00:05:49.672 align:middle line:90% kind of closer to the image. 00:05:49.672 --> 00:05:52.130 align:middle line:84% We can change, for example, the brightness and the contrast 00:05:52.130 --> 00:05:54.950 align:middle line:84% so it's easier to separate the foreground from the background. 00:05:54.950 --> 00:05:58.180 align:middle line:84% And then we can calculate what we call the frame difference. 00:05:58.180 --> 00:06:00.800 align:middle line:10% So we take one frame and then the next frame 00:06:00.800 --> 00:06:03.260 align:middle line:10% and we subtract them mathematically from each other. 00:06:03.260 --> 00:06:05.090 align:middle line:10% And what you end up with is what we 00:06:05.090 --> 00:06:08.900 align:middle line:10% call a motion image that is showing what changed 00:06:08.900 --> 00:06:10.760 align:middle line:10% between these two frames. 00:06:10.760 --> 00:06:15.980 align:middle line:84% And then that is something you can look at as a video, 00:06:15.980 --> 00:06:18.020 align:middle line:84% so you can see only the parts in the image that 00:06:18.020 --> 00:06:19.240 align:middle line:90% changed over time. 00:06:19.240 --> 00:06:23.270 align:middle line:84% And this is a very common way to start to do an analysis. 00:06:23.270 --> 00:06:24.650 align:middle line:84% And then from that one, again, we 00:06:24.650 --> 00:06:27.110 align:middle line:84% can create what we call this motiongram. 00:06:27.110 --> 00:06:31.310 align:middle line:84% That's this representation over time of a motion sequence 00:06:31.310 --> 00:06:33.290 align:middle line:84% that's based kind of squeezing together 00:06:33.290 --> 00:06:36.980 align:middle line:84% each of the motion images and plotting them over time. 00:06:36.980 --> 00:06:40.640 align:middle line:10% It's also possible to look at what we call a motion history 00:06:40.640 --> 00:06:44.630 align:middle line:10% video, where you can see kind of traces 00:06:44.630 --> 00:06:48.230 align:middle line:10% of the motion of a person over time as we see here. 00:06:48.230 --> 00:06:51.050 align:middle line:10% With different types of philtres on top. 00:06:51.050 --> 00:06:54.320 align:middle line:10% So this we can kind of tailor to the particular motion 00:06:54.320 --> 00:06:55.400 align:middle line:10% in question. 00:06:55.400 --> 00:06:57.850 align:middle line:10% And together then, a motiongram is 00:06:57.850 --> 00:06:59.600 align:middle line:10% kind of a representation that can give you 00:06:59.600 --> 00:07:03.830 align:middle line:10% a sense of how the body is moving in time and space. 00:07:03.830 --> 00:07:05.690 align:middle line:10% While in this case, here, we can look 00:07:05.690 --> 00:07:12.980 align:middle line:10% at a continuous video, where we see how the motion is changing 00:07:12.980 --> 00:07:14.600 align:middle line:10% spatially. 00:07:14.600 --> 00:07:16.513 align:middle line:10% And a course, based on this again, 00:07:16.513 --> 00:07:18.680 align:middle line:10% it's possible to calculate various types of features 00:07:18.680 --> 00:07:21.490 align:middle line:10% that can be used in quantitative measurements. 00:07:21.490 --> 00:07:24.800 align:middle line:10% So we often like to work within both quantitative and 00:07:24.800 --> 00:07:27.770 align:middle line:10% qualitative video analysis approaches 00:07:27.770 --> 00:07:30.140 align:middle line:10% and use these types of visualisation techniques 00:07:30.140 --> 00:07:34.940 align:middle line:10% as a guide to help us with finding what is important. 00:07:34.940 --> 00:07:39.200 align:middle line:84% So it's possible to do this type of video analysis on its own, 00:07:39.200 --> 00:07:42.110 align:middle line:84% but we often combine it with motion capture 00:07:42.110 --> 00:07:44.780 align:middle line:84% so that we can get the best of both worlds. 00:07:44.780 --> 00:07:47.150 align:middle line:84% That is, a very high level of accuracy and precision 00:07:47.150 --> 00:07:49.160 align:middle line:84% from the motion capture system, and then 00:07:49.160 --> 00:07:55.240 align:middle line:84% a more holistic and global view from the video recordings. 00:07:55.240 --> 00:08:01.000 align:middle line:90%