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Roman White, Lana Del Rey, "National Anthem" dir. Anthony Mandler, Twenty-plus Harlemites in their baggy, earlys best rocking at canted angles away from the camera, arranged on courtyard steps -- this is a movement. This is what power looks like. Truly, did we dream this? Snoop Dogg feat. Paul Hunter, Orange Caramel, "My Copycat" dir. Digipedi, Drake feat.
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Tracks 2 and 4 comprised the break routine, while tracks 1 and 3 served as start-up and control tracks with little structural development. The questionnaire showed that most of the participants were not familiar with any of the tracks. A web-based questionnaire was sent to the participants following the recording session and completed over the next few days.
In it the participants were asked to rate the music tracks used in the dance study according to pleasure and familiarity, and they were also asked to describe any particular musical characteristics associated with their experienced pleasure. The four tracks from the DJ mix were embedded as audio files in the questionnaire to jog the participants' memories, and they were encouraged to use headphones while listening to the excerpts.
The questionnaire also asked about demographic information such as education, formal and informal musical training, and music listening and dancing habits. The dancing of the participants was tracked and recorded using an infrared, marker-based motion capture system from Qualisys Oqus Each participant was equipped with two small non-obtrusive reflective markers: one marker was positioned on top of the head to pick up the overall movement of the body, while the other was attached to the wrist of the dominant hand to track the extremities of the body. Thus a total of 32 reflective markers were captured, at a frame rate of Hz.
An effort went into transforming the motion capture lab into a setting that resembled a club. For example, the main lights in the room were switched off, and five rotating and color-changing light effects machines were installed to move in synchronization to the beat of the music. The motion capture lab 1 before light adjustments, 2 after light adjustments, and 3 during the dance session. All 16 participants were recorded together in a dance session that lasted around 15 minutes. The participants were instructed to dance as they would have done in an actual club setting.
They were further instructed to remain within the capture area, which was covered with a black carpet that measured approximately 5 by 3. As mentioned previously, ecological validity was our main concern in the design of the experiment's setting. The experiment was carried out in the evening on a warm summer day using real and loud dance music. We tried to make the whole experience feel as natural as possible, even though the participants had to give their consent and be equipped with markers when they entered the space. Because they were restricted to a small dance space, they had to dance relatively close to one another, just as they would in an actual club setting.
The participants reported that they found the experiment enjoyable and fun. The overall results of the analyses indicate correspondences between the participants' quantity of motion, their self-reported experience of pleasure, and the structural conventions in the music. We will consider the associations between body movements and musical features before exploring the associations between affective engagement and musical features.
In the analysis of the motion capture data, we focused mainly on the global movement of the whole group with respect to specific musical features. This was a pragmatic solution, as it turned out to be difficult to track individual subjects over time due to marker occlusion. The participants danced very close together, many of them moved quite a lot, and many of them also raised their arms during the recordings.
This made it difficult to satisfactorily identify individual markers over the entire recording, since there are so many individual motion trajectories in the dataset.
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Marker-based motion capture systems like ours are mainly used to track individual people via multiple markers, and in these cases it is fairly straightforward to resolve marker occlusion problems by gap-filling trajectories that are close in time and space. In our current dataset, however, there were only two markers per person. Since the participants were dancing so close together and moving in all directions, it was not possible to use a proximity-based gap-filling technique.
Even though there were many broken motion trajectories in the dataset, the overall tracking percentage was satisfactory, so we decided to focus on the general movement of the group for this analysis. There the global quantity of motion QoM of each trajectory was calculated as the sum of the cumulative distance traveled for each marker in all directions XYZ divided by time, or, more precisely,.
We calculated the global QoM by summing the QoM of all trajectories and normalizing the value by the number of recorded markers P :.
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The plots in Figure 2 show how the group moved along with the four different tracks, with both the raw QoM data grey and the data smoothed with a second Savitzky-Golay filter black. The figure also presents an amplitude plot of the audio track, including a filtered root-mean-square RMS plot second Savitzky-Golay filter for reference.
There are, however, some interesting moments in the recording, most notably during tracks 2 and 4. Both of these tracks have break routines, and in both instances the plots show a sudden and large decrease followed by an increase in QoM after the drop. More gradual changes in the QoM of the dancers occur in the transitions between the tracks, which follow the same gradual dynamic changes in the music, due to the tracks being mixed into one another.
Looking more closely at the break routines, it is possible to see differences between the tracks, including the break routine and control tracks. It is clear that the change is largest for track 4 "Icarus" , which was also the track that the participants rated as "most pleasurable. Top: Plots of the raw grey and filtered black quantity of motion QoM for all subjects for the full dance session.