Published March 1, 2023 | Version 1.0.0

Time Series Data of Gaze, Head Pose, Hand Pose, and Object Positions for Object Approaches with a Given Intention

  • 1. Intelligent Sensor-Actuator-Systems Laboratory, Karlsruhe Institute of Technology
  • 2. ARSPECTRA

Description

This data set comprises time series data of gaze, head pose, hand pose, and object positions for object approaches with a given intention. The data was captured in the context of the following publication:

  • Michael Fennel, Serge Garbay, Antonio Zea, Uwe D. HanebeckIntention Estimation with Recurrent Neural Networks for Mixed Reality Environments, Proceedings of the 26th International Conference on Information Fusion (Fusion 2023) (under review)

A Microsoft Hololens 2 was used for recording the data at 60 fps under the modalities explained in detail in the above-mentioned paper.

The file names are structured as follows:

  • 1st/2nd:
    • The data with "1st" contains approaches to randomly placed objects on a grid, which are rendered in augmented reality. The user is informed about the object to approach using a visual cue. This corresponds to Section IV-A.
    • The data with "2nd" contains approaches to real objects placed statically in a room. The user is informed about the object to approach using a voice command.
  • unfiltered: Contains all approaches, including those where the user disrespects the given commands. Filtering is done as described in the paper.
  • train/val/test: The first dataset was split in a 70/20/10 ratio for training, validation, and test.

Each data set contains the following columns. In each approach, 5 objects numbered from i=0 to i=4 are present.

  • General:
    • time: in seconds
    • subject: consecutive subject number
    • handedness: left (1), right (0)
    • trial: consecutive trial number per subject
    • target_label: index of the object to approach (0 to 4)
  • Data in world coordinates:
    • head_{x,y,z}: head position
    • head_quat_{w,x,y,z}: head orientation quaternion
    • W_gaze_{x,y,z}: gaze direction
    • W_r_hand_{x,y,z}: right hand position
    • W_r_hand_quat_{w,x,y,z}: right hand orientation quaternion
    • W_l_hand_{x,y,z}: left hand position
    • W_l_hand_quat_{w,x,y,z}: left hand orientation quaternion
    • W_object_i_{x,y,z}: position of object i
    • W_object_i_quat {w,x,y,z}: orientation quaternion of object i
  • Data in egocentric coordinates (head coordinate system). This data is provided for convenience and can be derived from the other data:
    • gaze_{x,y,z}: gaze direction
    • r_hand_{x,y,z}: right hand position
    • r_hand_quat_{w,x,y,z}: right hand orientation quaternion
    • l_hand_{x,y,z}: left hand position
    • l_hand_quat_{w,x,y,z}: left hand orientation quaternion
    • object_i_{x,y,z}: position of object i
    • object_i_quat {w,x,y,z}: orientation quaternion of object i

Acknowledgment:

This work was supported by the ROBDEKON project of the German Federal Ministry of Education and Research.

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