@inproceedings{mason_iros_2018,
  title = {Human Activities Data Collection and Labeling using a Think-aloud Protocol in a Table Setting Scenario},
  author = {Mason, Celeste and Meier, Moritz and Ahrens, Florian and Fehr, Thorsten and Herrmann, Manfred and Putze, Felix and Schultz, Tanja},
  booktitle = {IROS 2018: Workshop on Latest Advances in Big Activity Data Sources for Robotics \& New Challenges},
  year={2018},
  address={Madrid, Spain},
  url={https://www.csl.uni-bremen.de/cms/images/documents/publications/mason_iros_2018.pdf},
  abstract={We describe our efforts in developing a Biosignals Acquisition Space and Environment (BASE) to acquire a large database of human everyday activities along with a procedure to automatically structure and label these high-dimensional data into a valuable resource for research in cognitive robotics. The final dataset is planned to consist of synchronously recorded biosignals from about 100 participants performing everyday activities while describing their task through use of think-aloud protocols. Biosignals encompass multimodal sensor streams of near and far speech \& audio, video, marker-based motion tracking, eye-tracking, as well as muscle and brain readings of humans performing everyday activities. This paper provides details of our pilot recordings carried out in the well established and scalable "table setting scenario." Besides presenting initial insights, the paper describes concurrent and retrospective think-aloud protocols and compares their usefulness toward automatic data segmentation and structuring.}
}