We have heard of face and voice recognition software programs that work to ensure the identity of someone. But, now researchers are indicating that the way you dance is something that is personally unique and can be used as a way to identify someone.
Regardless of the type of music used, a computer can identify a dancer because of their “dancing characteristics” with astounding accuracy. Researchers studying how music moves people both physically and metaphorically were surprised to discover the powerfulness of motion capture technology and how it can determine some features of behavior such as current mood, if you are extroverted, and at what degree can you sympathize with people.
The same kind of technology is utilized in the world of Hollywood.
Learn more about motion capture technology:
"We actually weren't looking for this result, as we set out to study something completely different," explains Dr. Emily Carlson, the first author of the study. "Our original idea was to see if we could use machine learning to identify which genre of music our participants were dancing to, based on their movements."
At the Centre for Interdisciplinary Music Research at the University of Jyväskylä in Finland, researchers analyzed the dancing of 73 participants to eight different genres: Blues, Country, Dance/Electronica, Jazz, Metal, Pop, Reggae and Rap. They specifically analyzed movements using machine learning to try to distinguish between the musical genres.
All the participants had to do was simply listen to the music and move any way they desired.
"We think it's important to study phenomena as they occur in the real world, which is why we employ a naturalistic research paradigm," says Professor Petri Toiviainen, the senior author of the study.
Although the computer algorithm was unsuccessful in identifying the musical genre, the discovery seemed to be much better—and that is how the computer can guess the dancing of each individual. "It seems as though a person's dance movements are a kind of fingerprint," says Dr. Pasi Saari, co-author of the study and data analyst. "Each person has a unique movement signature that stays the same no matter what kind of music is playing."
"There is a strong cultural association between Metal and certain types of movement, like headbanging," Emily Carlson says. "It's probable that Metal caused more dancers to move in similar ways, making it harder to tell them apart."
Will these results mean a future of dance-recognition software?
"We're less interested in applications like surveillance than in what these results tell us about human musicality," Carlson explains. "We have a lot of new questions to ask, like whether our movement signatures stay the same across our lifespan, whether we can detect differences between cultures based on these movement signatures, and how well humans are able to recognize individuals from their dance movements compared to computers. Most research raises more questions than answers," she concludes, "and this study is no exception."
Source: Science Daily