Analysing human behaviour and their trajectories in space from a social perspective

Repository containing the work in progress for the project Detecting Socially Occupied Spaces at the University of Münster.

Goal

This research aims to design a technological solution to interpret the socially occupied space automatically by using depth cameras.

Publications

• V. A. L. S. León and A. Schwering, "Detecting socially occupied spaces with depth cameras: evaluating location and body orientation as relevant social features," 2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2021, pp. 1-8, doi: 10.1109/IPIN51156.2021.9662607

• Sosa-Leon, V., Schwering, A., (2022). Evaluating Automatic Body Orientation Detection for Indoor Location from Skeleton Tracking Data to Detect Socially Occupied Spaces Using the Kinect v2, Azure Kinect and Zed 2i. Sensors 2022, 22, 3798. https://doi.org/10.3390/s22103798

Collaborators

• Angela Schwering
• Violeta Ana Luz Sosa-León