Abstract

Recently, the size of models for real-time rendering has been significantly increasing for realism, and many graphics applications are being developed in mobile devices with relatively insufficient hardware power. Therefore, improving rendering speed is still important in graphics. Back-face culling is one of the core speed-up techniques to remove the back-facing polygons that are not drawn in the result image. In this paper, we present a mesh clustering and reordering method based on normal coherence for efficient back-face culling at an earlier stage than the current method, which removes back faces after the vertex shader on the GPU. In the pre-computation, our method first vertically clusters the mesh into multiple stripes based on the latitude of the face normal vector and sorts each stripe in ascending order of longitude. At runtime, our method computes a potentially visible set of faces at the current camera view by excluding back faces from the clustered and reordered faces list, and draws only the potentially visible set. Experiments have shown that the rendering using our method is more efficient than traditional methods, especially for large and static models.

Highlights

  • Hidden surface removal or hidden surface determination has been studied since the very early days of computer graphics and has played a major role in improving performance.This is especially important for interactive or real-time applications, as the size of models has been drastically increasing for the realistic representation of objects

  • We present a mesh clustering and reordering method based on the normal vector coherence for a high-performance back-face culling

  • Our method renders 3D models efficiently by drawing only the potentially visible set (PVS), which excludes most of back faces in the CPU process

Read more

Summary

Introduction

Hidden surface removal or hidden surface determination has been studied since the very early days of computer graphics and has played a major role in improving performance. This is especially important for interactive or real-time applications, as the size of models has been drastically increasing for the realistic representation of objects. The general idea of these visibility culling methods is to save the computational resources for processing geometric primitives that do not contribute to the final image by excluding those primitives at an early stage of the graphics pipeline [1,2]. Geometric clustering is useful for visibility culling by processing adjacent primitives together [6–11]. Geometric primitives could be reordered [3,18], structured [19], or processed in the GPU [3,20] to improve efficiency of visibility culling

Methods
Results
Conclusion

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.