In this paper, we describe a novel methodology for dance learning and evaluation using multi-sensor and 3D gaming technology. The learners are captured during dancing, while an avatar visualizes their motion using fused input from multiple sensors. Motion analysis and fuzzy-logic are employed for the evaluation of the learners' performance against the performance of an expert. Specifically, a two level Fuzzy Inference System is proposed which uses as input low level skeletal data and high level motion recognition probabilities for the evaluation of dancer's performance. Tests with real dancers, both learners and experts, dancing Tsamiko, a very popular traditional Greek dance, are presented showing the potential of the proposed method. © 2014 Springer International Publishing.
CITATION STYLE
Kitsikidis, A., Dimitropoulos, K., Yilmaz, E., Douka, S., & Grammalidis, N. (2014). Multi-sensor technology and fuzzy logic for dancer’s motion analysis and performance evaluation within a 3D virtual environment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8513 LNCS, pp. 379–390). Springer Verlag. https://doi.org/10.1007/978-3-319-07437-5_36
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