Cost-driven framework for progressive compression of textured meshes

Abstract

Recent advances in digitization of geometry and radiometry generate in routine massive amounts of surface meshes with texture or color attributes. This large amount of data can be compressed using a progressive approach which provides at decoding low complexity levels of details (LoDs) that are continuously refined until retrieving the original model. The goal of such a progressive mesh compression algorithm is to improve the overall quality of the transmission for the user, by optimizing the rate-distortion trade-off. In this paper, we introduce a novel meaningful measure for the cost of a progressive transmission of a textured mesh by observing that the rate-distortion curve is in fact a staircase, which enables an effective comparison and optimization of progressive transmissions in the first place. We contribute a novel generic framework which utilizes the cost function to encode triangle surface meshes via multiplexing several geometry reduction steps (mesh decimation via half-edge or full-edge collapse operators, xyz quantization reduction and uv quantization reduction). This framework can also deal with textures by multiplexing an additional texture reduction step. We also design a texture atlas that enables us to preserve texture seams during decimation while not impairing the quality of resulting LODs. For encoding the inverse mesh decimation steps we further contribute a significant improvement over the state-of-the-art in terms of rate-distortion performance and yields a compression-rate of 22:1, on average. Finally, we propose a unique single-rate alternative solution using a selection scheme of a subset among LODs, optimized for

Progressive Compression of Triangle Meshes

“…The header is composed of a few parameters (position type, geometric predictor, quantization bits, and mesh Axis-Aligned Bounding-Box) and of the base mesh. The base mesh is encoded via a state-of-the-art single-rate compression algorithm from the Draco library [6,17] based on the Edgebreaker coding method [18] (as in the original CPM method).…”

“…Most of the existing approaches only deal with manifold triangle meshes and few can compress either polygonal or non-manifold meshes. There are two main kinds of progressive approaches: connectivity-based approaches [10,15,1,12,3,17] consider the mesh connectivity to guide the simplification, while geometry-based approaches [7,16] operate on the geometry using a spatial tree structure (octree or kd-tree) to conduct the simplification. In this paper, we describe an implementation of "Compressed Progressive Meshes" [15] (CPM for short) with several improvements in the stopping criteria and final encoding, as proposed in recent approaches [3,17].…”

Cloud-based XR Services: A Survey on Relevant Challenges and Enabling Technologies

“…Draco aims to improve the storage and transmission of 3D graphics by compressing meshes and point-cloud data. The huge impact of Draco is depicted in current bibliography, as it influences and drives the design of alternative compression/decompression techniques [52], [53], [54], [55], [56], [57], [58], [59], [60], [61]. The framework uses a kd-tree to efficiently store data corresponding to points, connectivity information, texture coordinates, color information, normals and any other generic attributes associated with geometry.…”

AliceVision Meshroom

“…Researchers' interests include such widely different applications as the streaming of 360-degree video that allows free movement of the viewer in 3 rotational and 3 translational dimensions (6DOF) [1,2] and adaptive point cloud streaming [3]. They study issues of latency during the interaction in virtual worlds [4] or the compression of meshes [5]. Due to the wide range of interests and the difficulty in creating content, there is little exchange in terms of content and tools that could help more researchers to join these investigations.…”