Virtual Multiresolution Screen Space Errors: Hierarchical Level-of-Detail (HLOD) Refinement Through Hardware Occlusion Queries

Abstract

We present a novelty metric to perform the refinement of a HLOD-based system that takes into account visibility information. The information is gathered from the result of a hardware occlusion query (HOQ) performed on the bounding volume of a given node in the hierarchy. Although the advantages of doing this are clear, previous approaches treat refinement criteria and HOQ as independent subjects. For this reason, HOQs have been used restrictively as if their result were Boolean. In contrast to that, we fully exploit the results of the queries to be able to take into account visibility information within refinement conditions. We do this by interpreting the result of a given HOQ as the virtual resolution of a screen space where the refinement decision takes place. Our new error metric is general enough to be employed in any HLOD-based system as the quantity that guides its refinement. Despite its simplicity, in our experiments we obtained a meaningful performance boost (compared to previous approaches) in the frame-rate with almost no loss in image quality