At this year’s CHI conference in Hamburg, we had the opportunity to share the latest findings from our DFG project „HopE“ with the HCI community. In our contribution, we present a methodological approach for analyzing walking trajectories. In the HopE project, we extract these trajectories from depth camera data in order to draw conclusions about the mobility behavior of users in front of our Ambient Surfaces installations.
Title of the paper
Exploring Mobility Behavior Around Ambient Displays Using Clusters of Multi-dimensional Walking Trajectories
Jan Schwarzer, Julian Fietkau, Laurenz Fuchs, Susanne Draheim, Kai von Luck, and Michael Koch
Spatial information has become crucial in ambient display research and helps to better understand how people behave in a display’s vicinity. Walking trajectories have long been used to uncover such information and tools have been developed to capture them anonymously and automatically. However, more research is needed on the level of automation during mobility behavior analyses. Particularly, working with depth-based skeletal data still requires significant manual effort to, for instance, determine walking trajectories similar in shape. To advance on this situation, we adopt both agglomerative hierarchical clustering and dynamic time warping in this research. To the best of our knowledge, both algorithms have so far not found application in our field. Using a multi-dimensional data set obtained from a longitudinal, real-world deployment, we demonstrate here the applicability and usefulness of this approach. In doing so, we contribute insightful ideas for future discussions on the methodological development in ambient display research.