Improving Cube-to-ERP Conversion Performance with Geometry Features of 360 Video Structure

Abstract

360 videos provide an omnidirectional view of the scene with extremely large data. Therefore, representing 360 videos with less data has become more and more important. Cube format is such a popular representation of 360 videos. However, we have to convert cube to Equirectangula(ERP) for displaying convenience. In this paper, we enhance Cube-to-ERP conversion performance by joint using Convolutional Neural Network(CNN) and classical interpolation method. The optimal threshold of boundary is derived according to geometry features of the cube-to-ERP format. This threshold is the guidance of how to combine CNN and classical interpolation method. Our experiment results prove that the derived threshold has a certain degree of guiding significance. Furthermore, we propose a new evaluation criterion with the help of Marsaglia model. It is much easier and more accurate to evaluate geometry conversion process.