TY - GEN
T1 - Human Gaze and Head Rotation during Navigation, Exploration and Object Manipulation in Shared Environments with Robots
AU - Schreiter, Tim
AU - Rudenko, Andrey
AU - Magnusson, Martin
AU - Lilienthal, Achim J.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The human gaze is an important cue to signal intention, attention, distraction, and the regions of interest in the immediate surroundings. Gaze tracking can transform how robots perceive, understand, and react to people, enabling new modes of robot control, interaction, and collaboration. In this paper, we use gaze tracking data from a rich dataset of human motion (THÖR-MAGNI) to investigate the coordination between gaze direction and head rotation of humans engaged in various indoor activities involving navigation, interaction with objects, and collaboration with a mobile robot. In particular, we study the spread and central bias of fixations in diverse activities and examine the correlation between gaze direction and head rotation. We introduce various human motion metrics to enhance the understanding of gaze behavior in dynamic interactions. Finally, we apply semantic object labeling to decompose the gaze distribution into activity-relevant regions.
AB - The human gaze is an important cue to signal intention, attention, distraction, and the regions of interest in the immediate surroundings. Gaze tracking can transform how robots perceive, understand, and react to people, enabling new modes of robot control, interaction, and collaboration. In this paper, we use gaze tracking data from a rich dataset of human motion (THÖR-MAGNI) to investigate the coordination between gaze direction and head rotation of humans engaged in various indoor activities involving navigation, interaction with objects, and collaboration with a mobile robot. In particular, we study the spread and central bias of fixations in diverse activities and examine the correlation between gaze direction and head rotation. We introduce various human motion metrics to enhance the understanding of gaze behavior in dynamic interactions. Finally, we apply semantic object labeling to decompose the gaze distribution into activity-relevant regions.
UR - http://www.scopus.com/inward/record.url?scp=85206976290&partnerID=8YFLogxK
U2 - 10.1109/RO-MAN60168.2024.10731190
DO - 10.1109/RO-MAN60168.2024.10731190
M3 - Conference contribution
AN - SCOPUS:85206976290
T3 - IEEE International Workshop on Robot and Human Communication, RO-MAN
SP - 1258
EP - 1265
BT - 33rd IEEE International Conference on Robot and Human Interactive Communication, ROMAN 2024
PB - IEEE Computer Society
T2 - 33rd IEEE International Conference on Robot and Human Interactive Communication, ROMAN 2024
Y2 - 26 August 2024 through 30 August 2024
ER -