- Title: Avatars help scientists find best female dance moves
- Date: 6th April 2017
- Summary: (SOUNDBITE) (English) DR. NICK NEAVE, ASSOCIATE PROFESSOR OF EVOLUTIONARY PSYCHOLOGY AT NORTHUMBRIA UNIVERSITY, SAYING: "Our study found that there were four things that characterise high quality female dance. The first was large movements of the hips. The second was the ability to keep in time, to a rhythm. The third was asymmetric movements of the arms, so that the arms were doing something slightly different to one another; and the fourth was the same thing for the legs - that the legs were each doing something slightly different." VARIOUS OF NEAVE'S TEAM LOOKING AT AVATAR MOTION CAPTURE CAMERA NEAVE'S TEAM LOOKING AT AVATAR
- Embargoed: 20th April 2017 15:37
- Keywords: dance dancing dancer avatar fertility Northumbria University
- Location: NEWCASTLE, ENGLAND, UK / ANIMATION
- City: NEWCASTLE, ENGLAND, UK / ANIMATION
- Country: United Kingdom
- Topics: Science
- Reuters ID: LVA0086B9IFKR
- Aspect Ratio: 16:9
- Story Text: A study using video avatars of female volunteers dancing has helped researchers pinpoint what they say are the dance floor moves most appealing to heterosexual males.
Researchers led by Dr. Nick Neave, associate professor of evolutionary psychology at Northumbria University, filmed 39 female students aged 18-25 dancing to the drumbeat of a Robbie Williams song.
Motion-capture technology was used to record their moves, which the researchers then mapped onto a digital avatar to ensure that the heterosexual men and women rating each dancer judged them purely by their dance floor proficiency.
"We found that if we ask people to rate other people when they dance they get distracted by other features - the physical appearance, the clothing, the ethnicity," explained Neave. "We wanted to remove those possible biases and have people focus on the actual movement, so we turned people into a featureless avatar."
PhD student Chris McCarty then tweaked the images to give each dancer similar physical characteristics.
"After we got a wire frame diagram of our subjects dancing, we normalise their height and build using a 3D model. To do this we transfer this into an animation package that you would typically see in (video) games," said McCarty.
A group of 200 volunteers - 57 men and 143 women - all heterosexual and over the age of 18, were asked to rate the dancing on a scale of 1-7.
"Our study found that there were four things that characterise high quality female dance," said Neave. "The first was large movements of the hips. The second was the ability to keep in time, to a rhythm. The third was asymmetric movements of the arms, so that the arms were doing something slightly different to one another; and the fourth was the same thing for the legs."
The most appealing female moves were found to be hip-swinging with leg and arm movement. In an earlier study Neave's team found that men who tilted and twisted their neck and torsos were deemed to be good dancers.
The most popular male dance moves were centralised in the upper body.
"We think that when males dance they're showing off their strength, not to females particularly but especially to other males. They're showing off who's the boss and who's in charge," said Neave.
"We suspect that female dance moves signify the same kind of things, but in relation to things like their fertility, their health, their reproductive status. We also think they'll be giving off these signals to males and to females."
Neave hopes future research will find "close links between a female's health, reproductive quality and fertility, and her dance moves."
He hopes that understanding the characteristics of good dancing will help scientists understand more about its evolutionary function.
Female PhD student Sarah Allen, whose own dancing was turned into an avatar to demonstrate the technology to Reuters, said that although she danced mainly to have fun and enjoy the music, "there is definitely an aspect of wanting to look good and maybe catch the eye of the opposite sex."
The study was published in online, open access journal Scientific Reports. - Copyright Holder: FILE REUTERS (CAN SELL)
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