  This paper describes the design and evaluation of the vision-based
classification of social gestures, such as handshake, hug, high-five, etc. This
is a component of the mediated social touch systems, which can be incorporated
into ShareTable and SqueezeBands system to achieve automated gestures
recognition and transmission of the touch between the users in real time. The
results from our pilot study show the recognition accuracy of each gestures,
and they indicate that significant future work is necessary to improve its
practical feasibility in the mediated social touch applications.
