Hierarchical Rendering System Based on Viewpoint Prediction in Virtual Reality

Abstract

Virtual reality (VR) systems use multi-modal interfaces to explore three-dimensional virtual worlds. During exploration, the user may look at different objects of interest or in different directions. The field of view of human vision is 135$^{\circ }\times 160^{\circ }$, but the one requiring the highest resolution is only in 1.5$^{\circ }\times 2^{\circ }$. It is estimated that in modern VR, only 4$\%$ of the pixel resources of the head-mounted display are mapped to the visual center. Therefore, allocating more computing resources to the visual center and allocating fewer viewpoint prediction rendering techniques elsewhere can greatly speed up the rendering of the scene, especially for VR devices equipped with eye trackers. However, eye trackers as additional equipment may be relatively expensive and be harder to use, at the same time, there is considerable work to be done in the development of eye trackers and their integration with commercial head-mounted equipment. Therefore, this article uses an eye-head coordination model combined with the saliencey of the scene to predict the gaze position, and then uses a hybrid method of Level of Detail (LOD) and grid degeneration to reduce rendering time as much as possible without losing the perceived details and required calculations.