DeepDance: Motion capture data of improvised dance (2019)

When using this resource, please cite Wallace, B., Nymoen, K., Martin, C.P & Tøressen, J. (2022). DeepDance: Motion capture data of improvised dance (2019) (version 1.0). Zenodo 10.5281/zenodo.5838179 Abstract This dataset comprises full-body motion capture of dance as well as corresponding audio files. Nine dancers were recorded individually, improvising to six different audio files. The motion was captured in units of mm at 250Hz using a Qualisys infra-red optical system. The experiment was carried out at the University of Oslo in October 2019. For each dancer, 3 performances are recorded for each musical piece, resulting in 162 motion capture files. The dataset was collected for use as training data in deep learning for motion generation. This dataset also includes MATLAB code to visualize the motion capture files. Music Skarphedinsson, M. Wallace, B. (2019). “Song a” Skarphedinsson, M. Wallace, B. (2019). “Song b” Skarphedinsson, M. Wallace, B. (2019). “Song c” Skarphedinsson, M. Wallace, B. (2019). “Song d” Skarphedinsson, M. Wallace, B. (2019). “Song f” LaClair, J. Bounce. Jesse LaClair, (2018) Referenced here as “Song e” Data Description The following data types are provided: Motion (marker position): Recorded with Qualisys Track Manager and saved as tab-separated .tsv files. Stimuli: audio .wav files containing 1 minute of the tracks described above. Code: MATLAB script for visualizing the motion capture files. Post-processing: The motion capture files are downsampled to 30 fps. Body segments have been standardized across all dancers in the data set and normalized so that the root marker is set at the origin. For further details please see [2]. Acknowledgements This work was partially supported by the Research Council of Norway through its Centres of Excellence scheme, project number 262762. Conflicts of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

搜集汇总

背景与挑战

背景概述

DeepDance数据集包含9位舞者在6首音乐伴奏下的即兴舞蹈动作捕捉数据(250Hz采集，降采样至30fps)及对应音频文件，共162个动作文件，适用于舞蹈动作生成研究。数据集还提供MATLAB可视化代码和标准化处理后的动作数据。