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Casa Paganini - InfoMus
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Datasets

  • Multimodal Dataset of Lightness and Fragility


    The dataset is composed of short segments containing full-body movements of two expressive qualities: Lightness and Fragility.
    In total we collected 150 segments by 13 participants. The data consists of multiple 3D accelerometer data, video channels, respiration audio and EMG signals.
    The data (video, audio, IMU, EMG) can be freely used for research purposes. It can be downloaded here.

    The dataset is a part of the EU Project DANCE n 645553. DANCE investigates how affective and relational qualities of body movement can be expressed, represented, and analyzed by the auditory channel.

    If you have used our dataset in your research please cite the work:
    Niewiadomski, R., Mancini, M., Cera, A., Piana, S., Canepa, C., Camurri, A., Does embodied training improve the recognition of mid-level expressive movement qualities sonification?, in Journal on Multimodal User Interfaces, ISBN/ISSN: 1783-8738, Dec, 2018
    doi: 10.1007/s12193-018-0284-0

  • MMLI - Multimodal Multiperson Corpus of Laughter in Interaction


    The Multimodal and Multiperson Corpus of Laughter in Interaction (MMLI) contains data of hilarious laughter with the focus on full-body movements. It contains nearly 500 segments of induced and interactive laughs from human triads. The dataset is composed of full-body motion capture data of subjects who participated in several social activities, e.g., playing social games such as "barbichette" or pictionary game, etc. 16 people partcipated in the recordings. The total duration of the segments is more than 70 minutes.
    The data consists of 3D body position information and multiple video channels. The motion data can be freely used for research purposes. It can be downloaded here.

    The corpus is a part of the EU FET Project ILHAIRE n 270780 dedicated to laughter analysis and synthesis.

    If you have used our dataset in your research please cite the work:
    Niewiadomski, R., Mancini, M., Varni, G., Volpe, G., Camurri, A., Automated Laughter Detection from Full-Body Movements, IEEE Transactions on, vol.46, no.1, pages 113-123, Feb. 2016.
    doi: 10.1109/THMS.2015.2480843

  • The Karate dataset focuses on full-body movements of athletes performing katas


    Katas are used in several martial arts to practice certain movements (e.g., kicking combinations) as well as to improve physical conditioning, muscle memory, focus/concentration, and balance.
    The Karate dataset is composed of 32 minutes of 3D MoCap data at 250 Hz performed by several athletes with the different levels of experience. Each kata was evaluated by 14 experienced raters. It can be downloaded here.

    If you have used our dataset in your research please cite the work:
    Niewiadomski, R., Kolykhalova, K., Piana, S., Alborno, P., Volpe, G., Camurri, A., Analysis of Movement Quality in Full-Body Physical Activities, ACM Transaction on Interactive Intelligent Systems.
    doi: 10.1145/3132369