Your dance moves are just as unique as your fingerprints
Study also finds your identity is more easily detected by computers because of it
PHOTO: FILE
In cities like Beijing or London, it’s hard to go anywhere without being filmed. Unfortunately, if you were planning on dancing your way through such heavily surveyed place to avoid detection, a new study finds you would actually be making yourself easier to identify.
Researchers from Finland say that every single person has their own unique way of dancing and computers are able to ascertain the identity of dancers with startling accuracy, reported Outlook India.
According to the research team, the vast majority of people maintain a uniform uniqueness to their dancing style. It’s this ever present personality in each of move that makes it easy for computers to ID us.
Over the past few years, the study’s authors have been using the same motion capture technology used in Hollywood to analyse people’s dance moves and what they can tell us about them. They’ve noted that dance moves can provide a whole lot of information about a person, such as if they are extroverted, neurotic, what type of mood they happen to be in, and even how much they empathise with others.
“We actually weren’t looking for this result, as we set out to study something completely different,” explained first study author Dr Emily Carlson. “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.”
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In total, 73 dancers took part in the experiment. Each was motion-captured as they danced to eight different musical genres. They were told to dance in whatever way felt natural.
“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.
But the machine learning algorithm actually wasn’t very good at identifying the musical genres, only offering a correct guess about 30% of the time. However, the computer was much better at identifying the dancers based on their movements. Among the 73 participants, the computer accurately determined who was dancing 94% of the time.
Researchers also noted that of all the studied musical genres, the computer had the hardest time identifying people who were dancing to metal. “There is a strong cultural association between metal and certain types of movement, like headbanging,” Dr Carlson explained. “It’s probable that metal caused more dancers to move in similar ways, making it harder to tell them apart.”
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Researchers from Finland say that every single person has their own unique way of dancing and computers are able to ascertain the identity of dancers with startling accuracy, reported Outlook India.
According to the research team, the vast majority of people maintain a uniform uniqueness to their dancing style. It’s this ever present personality in each of move that makes it easy for computers to ID us.
Over the past few years, the study’s authors have been using the same motion capture technology used in Hollywood to analyse people’s dance moves and what they can tell us about them. They’ve noted that dance moves can provide a whole lot of information about a person, such as if they are extroverted, neurotic, what type of mood they happen to be in, and even how much they empathise with others.
“We actually weren’t looking for this result, as we set out to study something completely different,” explained first study author Dr Emily Carlson. “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.”
Men are more emotional at work than women, study confirms
In total, 73 dancers took part in the experiment. Each was motion-captured as they danced to eight different musical genres. They were told to dance in whatever way felt natural.
“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.
But the machine learning algorithm actually wasn’t very good at identifying the musical genres, only offering a correct guess about 30% of the time. However, the computer was much better at identifying the dancers based on their movements. Among the 73 participants, the computer accurately determined who was dancing 94% of the time.
Researchers also noted that of all the studied musical genres, the computer had the hardest time identifying people who were dancing to metal. “There is a strong cultural association between metal and certain types of movement, like headbanging,” Dr Carlson explained. “It’s probable that metal caused more dancers to move in similar ways, making it harder to tell them apart.”
Have something to add to the story? Share it in the comments below.