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  1. 1

    Experimental exploration of artificial intelligence and ADAMS simulation technology in the teaching of vertical hoop upward throw in rhythmic gymnastics

    Ren, Q., Ma, Z.
    Published in PLOS ONE (2025)
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  2. 2

    From beats to scores: a multi-modal framework for comprehensive figure skating assessment

    Wang, F., Wang, Q., Chen, D.
    Published in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (2025)
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  3. 3

    A wearable system for jump detection in inline figure skating

    Panfili, A., Spanò, A., Cortesi, A.
    Published in Sensors (2022)
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  4. 4

    Modern Methods of fatigue assessment

    Volkova, Y.
    Published in Slobozhanskyi herald of science and sport (2020)
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  5. 5

    Multi-technology correction based 3D human pose estimation for jump analysis in figure skating

    Tian, L., Cheng, X., Honda, M., Ikenaga, T.
    Published in Proceedings (2020)
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  6. 6

    Tonight we improvise! Real-time tracking for human-robot improvisational dance

    Jochum, E., Derks, J.
    Published in Proceedings of the 6th International Conference on Movement and Computing (2019)
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  7. 7

    First steps in dance data science: educational design

    Bergner, Y., Mund, S., Chen, O., Payne, W.
    Published in Proceedings of the 6th International Conference on Movement and Computing (2019)
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  8. 8

    Shifting spaces: using defamiliarization to design choreographic technologies that support co-creation

    Carlson, K., Fdili Alaoui, S., Corness, G., Schiphorst, T.
    Published in Proceedings of the 6th International Conference on Movement and Computing (2019)
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  9. 9

    BalOnSe: Ballet ontology for annotating and searching video performances

    El Raheb, K., Papapetrou, N., Katifori, V., Ioannidis, Y.
    Published in Proceedings of the 3rd International Symposium on Movement and Computing (2016)
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  10. 10

    The dancer in the eye: towards a multi-layered computational framework of qualities in movement

    Camurri, A., Volpe, G., Piana, S., Mancini, M., Niewiadomski, R., Ferrari, N., Canepa, C.
    Published in Proceedings of the 3rd International Symposium on Movement and Computing (2016)
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  11. 11

    Towards a multimodal repository of expressive movement qualities in dance

    Piana, S., Coletta, P., Ghisio, S., Niewiadomski, R., Mancini, M., Sagoleo, R., Volpe, G., Camurri, A.
    Published in Proceedings of the 3rd International Symposium on Movement and Computing (2016)
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  12. 12

    Using interactive machine learning to sonify visually impaired dancers' movement

    Katan, S.
    Published in Proceedings of the 3rd International Symposium on Movement and Computing (2016)
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  13. 13

    3D annotation in contemporary dance: enhancing the creation-tool video annotator

    Ribeiro, C., Kuffner, R., Fernandes, C., Pereira, J.
    Published in Proceedings of the 3rd International Symposium on Movement and Computing (2016)
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  14. 14

    A web-based system for annotation of dance multimodal recordings by dance practitioners and experts

    El Raheb, K., Kasamoulis, A., Katifori, A., Rezkalla, M., Ioannidis, Y.
    Published in Proceedings of the 5th International Conference on Movement and Computing (2018)
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  15. 15

    Towards a model of nonverbal leadership in unstructured joint physical activity

    Niewiadomski, R., Chauvigne, L., Mancini, M., Camurri, A.
    Published in Proceedings of the 5th International Conference on Movement and Computing (2018)
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  16. 16

    Sketches vs skeletons: video annotation can capture what motion capture cannot

    Gillies, M., Brenton, H., Yee-King, M., Grimalt-Reynes, A., d'Inverno, M.
    Published in Proceedings of the 2nd International Workshop on Movement and Computing (2015)
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  17. 17

    Dynamic dance warping: Using dynamic time warping to compare dance movement performed under different conditions

    Ferguson, S., Schubert, E., Stevens, J. C.
    Published in Proceedings of the 2014 International Workshop on Movement and Computing (2014)
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  18. 18

    Potential competitive success rating mathematical model for elite rhythmic gymnasts

    Zakharyeva, N. N., Yashkina, E. N., Konyaev, I. D.
    Published in Theory and Practice of Physical Culture (2017)
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  19. 19

    Mathematical model of the skateboard

    Kuleshov, A. S.
    Published in ISBS - Conference Proceedings Archive (Konstanz) (2006)
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  20. 20

    ZUR BEURTEILUNG DER LEISTUNGSENTWICKLUNG IM EISKUNSTLAUF DER FRAUEN WAEHREND DES OLYMPIAZYKLUS 1984/88 AUF DER BASIS EINES MATHEMTISCH-STATISTISCHEN ZYKLUSMODELLS

    Kral, K.
    Published in Training und Wettkampf (1990)
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