Vision-based system model for detecting violence against children

Abstract

We present in this paper a machine learning model for detecting violence against children. This model, which uses skeletal data acquired by depth sensors achieved a high accuracy violence detection rate of 99.03 %.In sum, this research method presents: • First ML-based method for detecting most common child abuses, which keeps the privacy of people by using only skeleton joints data. • The model has only two classes (violent action, non-violent action). • The model can be a base for other researches and implementations in schools by school psychologists and counselors.

Keywords

• Reduced skeletal features-based model
• Classification
• Depth sensor
• k-NN
• Technology in society