Social Groups Detection by Using Support Vector Machine in Video

Document Type : Persian Original Article

Authors

Department of Electrical and Computer Engineering, University of Birjand, Birjand, Iran

Abstract

Detecting social groups is one of important and complex problems which has been concerned recently. Detecting social groups and relation between group members will be necessary for human robots in near future. Databases have some information including trajectories and also labels of members. The target is to detect social groups that contains at least two people or detecting individual motion of the persons. In the proposed method, for detecting social groups, physical distance, temporal causality and shape similarity features are used. The required time to extract these features is lower than the other suggested features. In addition to accuracy, the effectiveness of the proposed method in terms of required time for training and testing data is also examined. Lower required time provides greater ability to implement for human robots. The proposed method provides acceptable results in valid databases and is compared to existing methods in terms of statistical results and the required time.

Keywords