Real-Time Large Crowd Rendering with Efficient Character and Instance Management on GPU

Author:

Dong Yangzi1ORCID,Peng Chao1ORCID

Affiliation:

1. Department of Computer Science, University of Alabama in Huntsville, Huntsville, AL 35899, USA

Abstract

Achieving the efficient rendering of a large animated crowd with realistic visual appearance is a challenging task when players interact with a complex game scene. We present a real-time crowd rendering system that efficiently manages multiple types of character data on the GPU and integrates seamlessly with level-of-detail and visibility culling techniques. The character data, including vertices, triangles, vertex normals, texture coordinates, skeletons, and skinning weights, are stored as either buffer objects or textures in accordance with their access requirements at the rendering stage. Our system preserves the view-dependent visual appearance of individual character instances in the crowd and is executed with a fine-grained parallelization scheme. We compare our approach with the existing crowd rendering techniques. The experimental results show that our approach achieves better rendering performance and visual quality. Our approach is able to render a large crowd composed of tens of thousands of animated instances in real time by managing each type of character data in a single buffer object.

Funder

National Science Foundation

Publisher

Hindawi Limited

Subject

Computer Graphics and Computer-Aided Design,Human-Computer Interaction,Software

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