Synchronized Multimodal Recording of a Table Setting Dataset
by , , , ,
Abstract:
We present here a description of our initial efforts in developing a Biosignal Acquisition Space and Environment (BASE) to collect a large open access dataset of human everyday activities. The final dataset is planned to consist of synchronously recorded biosignals from 100 participants performing everyday activities while describing their task through use of think-aloud protocols. Biosignals encompass six different modalities, with one first person and seven third person cameras, a nine camera motion capture system, one near distance speech microphone and one far distance room microphone, four channel EMG, 16 channel EEG and an eye tracker. The data is collected in the context of the EASE collaborative research center and is intended to benefit the robotics community. This paper provides details regarding the sensors, devices and software used for the data recording as well as insights into the recorded biosignal data streams.
Reference:
Synchronized Multimodal Recording of a Table Setting Dataset (Moritz Meier, Celeste Mason, Robert Porzel, Felix Putze, Tanja Schultz), In IROS 2018: Workshop on Latest Advances in Big Activity Data Sources for Robotics & New Challenges, 2018.
Bibtex Entry:
@inproceedings{meier_iros_2018,
  title = {Synchronized Multimodal Recording of a Table Setting Dataset},
  author = {Meier, Moritz and Mason, Celeste and Porzel, Robert and Putze, Felix and Schultz, Tanja},
  booktitle = {IROS 2018: Workshop on Latest Advances in Big Activity Data Sources for Robotics \& New Challenges},
  year = {2018},
  url={https://www.csl.uni-bremen.de/cms/images/documents/publications/meier_iros_2018.pdf},
  address={Madrid, Spain},
  abstract={We present here a description of our initial efforts in developing a Biosignal Acquisition Space and Environment (BASE) to collect a large open access dataset of human everyday activities. The final  dataset  is  planned  to consist of synchronously recorded biosignals from 100 participants performing everyday activities  while  describing  their  task  through  use  of  think-aloud protocols. Biosignals encompass six different modalities, with one first person and seven third person cameras, a nine camera motion capture system, one near distance speech microphone and one far distance room microphone, four channel EMG, 16 channel EEG and an eye tracker. The data is collected in the context of the EASE collaborative research center and is intended to benefit the robotics community. This paper provides details regarding the sensors, devices and software used for the data recording as well as insights into the recorded biosignal data streams.}
}