Fast vector quantization for efficient rendering of compressed point-clouds

Abstract

We present a point-cloud compression algorithm that allows fast parallel decompression on the GPU suitable for interactive applications. The algorithm is based on vector quantization of an atlas of height-fields that have been sampled over primitive shapes which approximate the geometry. We introduce novel vector quantization acceleration techniques to facilitate fast compression as well. We achieve bitrates of less than four bits per normal-equipped point. Our method enables hole-free level-of-detail point rendering. We also show that using only up to two bits per point, high-quality renderings can still be obtained if normals are estimated in image-space. Even lower bitrates are obtained for storage on disk if arithmetic coding is used.