Motion-based control is gaining popularity, and motion gestures form a complementary modality in human-computer interactions. To achieve more robust user independent motion gesture recognition in a manner analogous to automatic speech recognition, we need a deeper understanding of the motions in gesture, which arouses the need for a 6D motion gesture database. In this work, we present a database that contains comprehensive motion data, including the position, orientation, acceleration, and angular speed, for a set of common motion gestures performed by different users. We hope this motion gesture database can be a useful platform for researchers and developers to build their recognition algorithms as well as a common test bench for performance comparisons. Associated codes with the dataset along with instructions may be found on our GitHub page at https://github.com/olivesgatech/6DMG.


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    Title :

    6DMG: A 6D Motion Gesture Database


    Contributors:

    Publication date :

    2020-06-10



    Type of media :

    Research Data


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    004 / 629




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