Hardware-Compatible Vertex Compression Using Quantization and Simplification

Abstract

We present a vertex compression technique suitable for efficient decompression on graphics hardware. Given a user-specified number of bits per vertex, we automatically allocate bits to vertex attributes for quantization to maximize quality, guided by an image-space error metric. This allocation accounts for the constraints of graphics hardware by packing the quantized attributes into bins associated with the hardware's vectorized vertex data elements. We show that this general approach is also applicable if the user specifies a total desired model size. We present an algorithm that integrally combines vertex decimation and attribute quantization to produce the best quality model for a user-specified data size. Such models have an appropriate balance between the number of vertices and the number of bits per vertex. Vertex data is transmitted to and optionally stored in video memory in the compressed form. The vertices are decompressed on-the-fly using a vertex program at rendering time. Our algorithms not only work well within the constraints of current graphics hardware but also generalize to a setting where these constraints are relaxed. They apply to models with a wide variety of vertex attributes, providing new tools for optimizing space and bandwidth constraints of interactive graphics applications.