3CPS: A novel supercompression for the delivery of 3D object textures

Abstract

The growing popularity of applications based on 3D rendering, such as visual effects, gaming, augmented and virtual reality, calls for the development of new solutions for the delivery of 3D objects, in particular textures. The format of texture images, which capture the characteristics of materials, has to address two constraints. First, the delivery on the Internet imposes a reduction of the image size. Second, because of memory limitations, the processing by the rendering engine is done in the GPU by extracting small areas of the image only. The format of texture images should thus enable the random-access feature for independent processing of small blocks of the images, called texels, which negatively affects the texture compression performance and, therefore, the network delivery. We propose 3CPS, a novel solution for the compression and delivery of texture images. In 3CPS, the texture image is compressed three times: first, at the authoring side, by a traditional texture compression technique; second, still at the authoring side, by a state-of-the-art image compression technique for better network delivery; third, at the client side, the received image is re-compressed by a texture image technique for better GPU processing. Our original idea leverages the fact that the image at the client side has already been converted into a format that can be easily transformed by the client for GPU processing. The last compression is thus expected to be much faster than usual. In this paper, we introduce this concept, propose a fast and efficient algorithm for the last re-compression, and demonstrate the advantages of our solution by performing an extensive evaluation on real data sets. In particular, we show that 3CPS competes well with Basis supercompression, which is evaluated for the first time.