Processed-Data for ConfLab: A Rich Multimodal Multisensor Dataset of Free-Standing Social Interactions In-the-Wild

Datacite citation style:
Raman, Chirag; Vargas Quiros, Jose; Tan, Stephanie; Islam, Ashraful; Gedik, Ekin et. al. (2022): Processed-Data for ConfLab: A Rich Multimodal Multisensor Dataset of Free-Standing Social Interactions In-the-Wild. Version 1. 4TU.ResearchData. dataset.
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
choose version: version 2 - 2022-10-10 (latest)
version 1 - 2022-06-08

This folder contains processed data (video and wearable sensors) for 16 mins
of interaction that were annotated for the Conflab dataset.

   ./video_segments contains the overhead video recordings for 5 cameras
   in MP4 files. These are split into 2 min segments, down-scaled to 960x540px,
   and denoised. The resulting files are the ones that were used to annotate poses
   and actions.

   For applications that require higher resolutions, the original video files in the
   "data_raw" folder are at 1920x1080 resolution and a script is provided to extract
   the same 2min segments.

   ./camera-calibration contains the camera instrinsic files obtained from: Camera extrinsic parameters
   can be calculated using the existing intrinsic parameters and the instructions
   in the multicamera-calibration repo. The coordinates in the image are provided
   by the crosses marked on the floor, which are visible in the video recordings.
   The crosses are 1m apart (=100cm).  

   contains one single dataframe with aggregated sensor information
   (accelerometer, gyroscope, magnetometer, rotation, proximity) per each person.
   The data has been interpolated and imputed at 50Hz (fixed). The code used to obtain
   these files from the raw data can be found at:

   This code can be used to preprocess larger segments of the werable data
   from the "data_raw" folder.

   Audio files are not part of this folder, but are provided in the "data_raw" file.

  • 2022-06-07 first online
  • 2022-06-08 published, posted
zipped files
  • NWO 639.022.606.
  • Aspasia grant associated with vidi grant 639.022.606.
TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Intelligent Systems

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