Random Accessible Mesh Compression Using Mesh Chartification

Choe, Sungyul; Kim, Junho; Lee, Haeyoung; Lee, Seungyong

doi:10.1109/tvcg.2008.64

Cited by 26 publications

(4 citation statements)

References 45 publications

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“…We propose laced wires , a random‐accessible, compressed mesh structure that combines the advantages of previous methods, namely laces [GLRL11] and wires [CKLL09, CH09]. Our representation is both compact and SIMD‐friendly, which is critical for end‐to‐end compression with high SIMD utilization.…”

Section: Compressed Meshlet Representationmentioning

confidence: 99%

“…Our representation is both compact and SIMD‐friendly, which is critical for end‐to‐end compression with high SIMD utilization. A wire is simply a sequence of vertices connected by edges [CKLL09]. We use wires to represent the boundary and the interior of a meshlet, such that two adjacent meshlets refer to the same wire at their shared boundary.…”

Section: Compressed Meshlet Representationmentioning

confidence: 99%

“…Finally, the border vertices can also be stored separately as vertex sequences ( wires ). The wires can be created from an existing subdivision into regions [CKLL09], or the regions can be created by recursively subdividing the mesh by placing wires [CH09]. In the latter case, we can traverse the hierarchical sub‐division to extract any desired region size.…”

Section: Related Workmentioning

confidence: 99%

“…Regions should have a finite spatial extent, and their primitive count should be chosen in a GPU-friendly manner. Ideally, a region corresponds to a meaningful part of an object [CG08,CKLL09], which can be loaded and decompressed individually.…”

Section: Introductionmentioning

confidence: 99%

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End‐to‐End Compressed Meshlet Rendering

Mlakar,

Steinberger,

Schmalstieg

2024

Computer Graphics Forum

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In this paper, we study rendering of end‐to‐end compressed triangle meshes using modern GPU techniques, in particular, mesh shaders. Our approach allows us to keep unstructured triangle meshes in GPU memory in compressed form and decompress them in shader code just in time for rasterization. Typical previous approaches use a compressed mesh format only for persistent storage and streaming, but must decompress it into GPU memory before submitting it to rendering. In contrast, our approach uses an identical compressed format in both storage and GPU memory. Hence, our compression method effectively reduces the in‐memory requirements of huge triangular meshes and avoids any waiting times on streaming geometry induced by the need for a decompression stage on the CPU. End‐to‐end compression also means that scenes with more geometric detail than previously possible can be made fully resident in GPU memory. Our approach is based on a novel decomposition of meshes into meshlets, i.e. disjoint primitive groups that are compressed individually. Decompression using a mesh shader allows de facto random access on the primitive level, which is important for applications such as selective streaming and fine‐grained visibility computation. We compare our approach to multiple commonly used compressed meshlet formats in terms of required memory and rendering times. The results imply that our approach reduces the required CPU–GPU memory bandwidth, a frequent bottleneck in out‐of‐core rendering.

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Section: Compressed Meshlet Representationmentioning

confidence: 99%

Section: Compressed Meshlet Representationmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

End‐to‐End Compressed Meshlet Rendering

Mlakar,

Steinberger,

Schmalstieg

2024

Computer Graphics Forum

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A Logistic Model for the Degradation of Triangle Mesh Normals

Yang

Ivrissimtzis

2012

Curves and Surfaces

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A hierarchical framework for large 3D mesh streaming on mobile systems

Park¹,

Lee

2014

Multimed Tools Appl

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Large 3D meshes are emerging as the new media for various applications but are still hard to use in mobile applications, due to the limited resources of mobile systems. This paper introduces a large 3D mesh streaming framework which flexibly deals with the limited resources of mobile systems and also provides a user with interactive controls and random accessibilities. To reduce resource usage, our framework presents a uniform mesh partitioning algorithm, in which each partition of a large mesh has the same number of vertices. Our uniform partitioning is based on a k-d tree clustering and extended for out-of-core meshes. A median search with heaps in the main memory is designed for faster external sorting. Large 3D meshes are transformed into a set of partitioned and simplified meshes in the server. For interactive 3D browsing, on mobile devices, our framework presents a mobile 3D viewer which is hierarchically designed with intuitive interfaces. A user can experience rapid 3D searches with 3D previews of simplified meshes. Multi touch inputs can control zooming and the level of detail in meshes automatically. Double tap touches enable a user to randomly select a region of a large mesh, and a set of partitions for the selected region will be streamed and displayed on a mobile client. As a result, our framework enables a user to browse large 3D meshes on a mobile system interactively, while optimizing system resource usage and protecting the original data in the server.

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Random Accessible Mesh Compression Using Mesh Chartification

Cited by 26 publications

References 45 publications

End‐to‐End Compressed Meshlet Rendering

End‐to‐End Compressed Meshlet Rendering

A Logistic Model for the Degradation of Triangle Mesh Normals

A hierarchical framework for large 3D mesh streaming on mobile systems

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