Estimation of body occlusion using deep learning for advanced intelligent video surveillance system

Abstract

This paper presents the development of a new method for the estimation and resolution of body occlusion using deep learning for an advanced intelligent video surveillance system. A generative adversarial network is used to estimate and reconstruct an image of a hidden part of the human body. Furthermore, an alternative learning approach using 3DCG that was developed in our previous study is adopted to create a large dataset for deep learning. Experimental results indicate that the proposed method performs well in the estimation of hidden parts of the human body using images of actual people.