The VISTA datasets, a combination of inertial sensors and depth cameras data for activity recognition

FIORINI, Laura, CORNACCHIA LOIZZO, Federica Gabriella, SORRENTINO, Alessandra, ROVINI, Erika, DI NUOVO, Alessandro and CAVALLO, Filippo (2022). The VISTA datasets, a combination of inertial sensors and depth cameras data for activity recognition. Scientific Data, 9: 218.

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Official URL: https://www.nature.com/articles/s41597-022-01324-3
Open Access URL: https://www.nature.com/articles/s41597-022-01324-3... (Published)
Link to published version:: https://doi.org/10.1038/s41597-022-01324-3
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    Abstract

    This paper makes the VISTA database, composed of inertial and visual data, publicly available for gesture and activity recognition. The inertial data were acquired with the SensHand, which can capture the movement of wrist, thumb, index and middle fingers, while the RGB-D visual data were acquired simultaneously from two different points of view, front and side. The VISTA database was acquired in two experimental phases: in the former, the participants have been asked to perform 10 different actions; in the latter, they had to execute five scenes of daily living, which corresponded to a combination of the actions of the selected actions. In both phase, Pepper interacted with participants. The two camera point of views mimic the different point of view of pepper. Overall, the dataset includes 7682 action instances for the training phase and 3361 action instances for the testing phase. It can be seen as a framework for future studies on artificial intelligence techniques for activity recognition, including inertial-only data, visual-only data, or a sensor fusion approach.

    Item Type: Article
    Identification Number: https://doi.org/10.1038/s41597-022-01324-3
    SWORD Depositor: Symplectic Elements
    Depositing User: Symplectic Elements
    Date Deposited: 19 May 2022 12:59
    Last Modified: 20 May 2022 15:04
    URI: http://shura.shu.ac.uk/id/eprint/30248

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