Object-human interaction pattern generating system using deep learning

Abstract

Robots have been widely used in many industries, from manufacturing to services. In addition, Human Activity Recognition technology has become important as robots become smart thanks to recent development of artificial intelligence. Future robots will be able to collaborate and co-work with humans. The main purpose of this article is to make robots understand human activities with a machine vision system. Analysing human activities is not only a problem of detecting human motion but also interaction between humans with objects. Therefore, we propose an integrated object-human interaction pattern generating system consisting of object detector, skeletal tracker, and object-human interaction detector. This system is designed to detect objects, track humans' skeletal movements in sequential images and analyse the interaction between object and human. Here, we focused on everyday human activities with related objects. The proposed system generates the object- human interaction patterns of each activity. © 2017 ICROS.