  This paper presents the design of deep learning architectures which allow to
classify the social relationship existing between two people who are walking in
a side-by-side formation into four possible categories --colleagues, couple,
family or friendship. The models are developed using Neural Networks or
Recurrent Neural Networks to achieve the classification and are trained and
evaluated using a database of readings obtained from humans performing an
accompaniment process in an urban environment. The best achieved model
accomplishes a relatively good accuracy in the classification problem and its
results enhance partially the outcomes from a previous study [1]. Furthermore,
the model proposed shows its future potential to improve its efficiency and to
be implemented in a real robot.
