TY - GEN
T1 - A feature importance study in ballet pose recognition with openpose
AU - Fourie, Margaux
AU - van der Haar, Dustin
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2020.
PY - 2020
Y1 - 2020
N2 - Movements of the human body can finally be recognised and analysed using computer vision technology. Ballet is an activity that involves various movements and specific poses of the body, making it an attractive candidate for computer vision applications. This paper proposes a feature importance study for determining which body parts play the most significant role in ballet pose recognition. The study is based on the use of OpenPose for feature extraction together with Support Vector Machine, Random Forest and Gradient Boosted Tree classifiers. Recognition accuracies above 95% suggest that the methods are not only feasible but exhibit excellent results. The results also indicate that the body parts that were the most significant for the classification of ballet poses were those situated at the extremities of the body such as the wrists and feet. The study addresses challenges within the ballet domain as it relates to both training and choreography. Furthermore, the study confirms that as technology expands into all areas of life, it is worthwhile to explore the possibilities within artistic fields.
AB - Movements of the human body can finally be recognised and analysed using computer vision technology. Ballet is an activity that involves various movements and specific poses of the body, making it an attractive candidate for computer vision applications. This paper proposes a feature importance study for determining which body parts play the most significant role in ballet pose recognition. The study is based on the use of OpenPose for feature extraction together with Support Vector Machine, Random Forest and Gradient Boosted Tree classifiers. Recognition accuracies above 95% suggest that the methods are not only feasible but exhibit excellent results. The results also indicate that the body parts that were the most significant for the classification of ballet poses were those situated at the extremities of the body such as the wrists and feet. The study addresses challenges within the ballet domain as it relates to both training and choreography. Furthermore, the study confirms that as technology expands into all areas of life, it is worthwhile to explore the possibilities within artistic fields.
KW - Ballet
KW - Computer vision
KW - Feature importance
KW - OpenPose
UR - http://www.scopus.com/inward/record.url?scp=85088742030&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-50334-5_16
DO - 10.1007/978-3-030-50334-5_16
M3 - Conference contribution
AN - SCOPUS:85088742030
SN - 9783030503338
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 243
EP - 254
BT - Artificial Intelligence in HCI - 1st International Conference, AI-HCI 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Proceedings
A2 - Degen, Helmut
A2 - Reinerman-Jones, Lauren
PB - Springer
T2 - 1st International Conference on Artificial Intelligence in HCI, AI-HCI 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020
Y2 - 19 July 2020 through 24 July 2020
ER -