An effective approach based on a subset of skeleton joints for two-person interaction recognition

Abstract

In this article, the problem of human interaction recognition is addressed. A novel methodology is presented to model the interaction between two people using a Kinect sensor. It is proposed to analyse the distances between a subset of skeleton joints to determine their contribution to the recognition of interaction. Subsequently, the most representative joints are taken into account for the formation of a pentagon for each person. Five Euclidean distances are extracted between the vertices of two pentagons corresponding to the people to analyse. Finally, the SVM is used for the recognition of human interaction. Experimental results demonstrate the effectiveness of this work compared to recently published proposals.