  We report on our effort to create a corpus dataset of different social
context situations in an office setting for further disciplinary and
interdisciplinary research in computer vision, psychology, and
human-robot-interaction. For social robots to be able to behave appropriately,
they need to be aware of the social context they act in. Consider, for example,
a robot with the task to deliver a personal message to a person. If the person
is arguing with an office mate at the time of message delivery, it might be
more appropriate to delay playing the message as to respect the recipient's
privacy and not to interfere with the current situation. This can only be done
if the situation is classified correctly and in a second step if an appropriate
behavior is chosen that fits the social situation. Our work aims to enable
robots accomplishing the task of classifying social situations by creating a
dataset composed of semantically annotated video scenes of office situations
from television soap operas. The dataset can then serve as a basis for
conducting research in both computer vision and human-robot interaction.
