Representational image. (iStock)
Seoul:
Love Korean pop dances? You may soon learn the art easily at home by tracking body joints, thanks to a virtual dance teacher developed by South Korean researchers.
Researchers Daijin Kim and his team at Pohang University of Science and Technology South Korea, successfully developed the precise 3D tracking of 15 human body joints using data of the human body and the relational information among human body joints.
Its tracking performance showed just a 4.5 cm error on average among 15 human body joints, the study reported.
In order to develop the virtual K-Pop dance teacher, the team selected a hundred K-POP dance routines that were performed by a professional dancer and collected the moves of 15 body joints of each dancing movement.
They then extracted the moves of 15 body joints from a dance learner using the precise 3D tracking of body joints and evaluated the average similarity between the body joint movements of the dance learner and those of the professional dancer.
They also developed a score monitoring method based on the similarity and represented how much each body part of a dance learner is deviated from the corresponding body part of a professional dancer.
The brightness of each body part specifies the similarity of dance movements of each body part, the researchers said.
The research was presented at ICIP 2015 - IEEE International Conference on Image Processing 2015 - in Quebec, Canada.
Researchers Daijin Kim and his team at Pohang University of Science and Technology South Korea, successfully developed the precise 3D tracking of 15 human body joints using data of the human body and the relational information among human body joints.
Its tracking performance showed just a 4.5 cm error on average among 15 human body joints, the study reported.
In order to develop the virtual K-Pop dance teacher, the team selected a hundred K-POP dance routines that were performed by a professional dancer and collected the moves of 15 body joints of each dancing movement.
They then extracted the moves of 15 body joints from a dance learner using the precise 3D tracking of body joints and evaluated the average similarity between the body joint movements of the dance learner and those of the professional dancer.
They also developed a score monitoring method based on the similarity and represented how much each body part of a dance learner is deviated from the corresponding body part of a professional dancer.
The brightness of each body part specifies the similarity of dance movements of each body part, the researchers said.
The research was presented at ICIP 2015 - IEEE International Conference on Image Processing 2015 - in Quebec, Canada.
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