triangle three-dimensional meshes have been widely used to represent 3D objects in several applications. These meshes are usually surfaces that require a huge amount of resources when they are stored, processed or tra...
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ISBN:
(纸本)9783642302374;9783642302381
triangle three-dimensional meshes have been widely used to represent 3D objects in several applications. These meshes are usually surfaces that require a huge amount of resources when they are stored, processed or transmitted. Therefore, many algorithms proposing an efficient compression of these meshes have been developed since the early 1990s. In this paper we propose a lossless method that compresses the connectivity of the mesh by using a valence-driven approach. Our algorithm introduces an improvement over the currently available valence-driven methods, being able to deal with triangular surfaces of arbitrary topology and encoding, at the same time, the topological information of the mesh by using Homological Spanning Forests. We plan to develop in the future (geo-topological) image analysis and processing algorithms, that directly work with the compressed data.
We focus on applications where a remote client needs to visualize or process a complex, manifold trianglemesh, M, but only in a relatively small, user controlled, Region of Interest (RoI) at a time. The client first ...
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We focus on applications where a remote client needs to visualize or process a complex, manifold trianglemesh, M, but only in a relatively small, user controlled, Region of Interest (RoI) at a time. The client first downloads a coarse base mesh, pre-computed on the server via a series of simplification passes on M, one per Level of Detail (LoD), each pass identifying an independent set of triangles, collapsing them, and, for each collapse, storing, in a Vertex Expansion Record (VER), the information needed to reverse the collapse. On each client initiated RoI modification request, the server pushes to the client a selected subset of these VERs, which, when decoded and applied to refine the mesh locally, ensure that the portion in the RoI is always at full resolution. The eBits approach proposed here offers state of the art compression ratios (using less than 2.5 bits per new full resolution RoI triangle when the RoI has more than 2000 vertices to transmit the connectivity for the selective refinements) and fine-grain control (allowing the user to adjust the RoI by small increments). The effectiveness of eBits results from several novel ideas and novel variations of previous solutions. We represent the VERs using persistent labels so that they can be applied in different orders within a given LoD. The server maintains a shadow copy of the client's mesh. To avoid sending IDs identifying which vertices should be expanded, we either transmit, for each new vertex, a compact encoding of its death tag the LoD at which it will be expanded if it lies in the RoI or transmit vertex masks for the RoI and its neighboring vertices. We also propose a three-step simplification that reduces the overall transmission cost by increasing both the simplification effectiveness and the regularity of the valences in the resulting meshes. (C) 2016 Elsevier Ltd. All rights reserved.
Lossless transmission of 3D meshes is a very challenging and timely problem for many applications, ranging from collaborative design to engineering, Additionally, frequent delays in transmissions call for progressive ...
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ISBN:
(纸本)158113374X
Lossless transmission of 3D meshes is a very challenging and timely problem for many applications, ranging from collaborative design to engineering, Additionally, frequent delays in transmissions call for progressive transmission in order for the end user to receive useful successive refinements of the final mesh. In this paper, we present a novel, fully progressive encoding approach for lossless transmission of trianglemeshes with a very fine granularity. A new valence-driven decimating conquest, combined with patch tiling and an original strategic retriangulation is used to maintain the regularity of valence. We demonstrate that this technique leads to good mesh quality, near-optimal connectivity encoding, and therefore a good rate-distortion ratio throughout the transmission. We also improve upon previous lossless geometry encoding by decorrelating the normal and tangential components of the surface. For typical meshes, our method compresses connectivity down to less than 3.7 bits per vertex, 40% better in average than the best methods previously reported [5, 18];we further reduce the usual geometry bit rates by 20% in average by exploiting the smoothness of meshes. Concretely, our technique can reduce an ascii VRML 3D model down to 1.7% of its size for a 10-bit quantization (2.3% for a 12-bit quantization) while providing a very progressive reconstruction.
Most systems that support visual interaction with 3D models use shape representations based on trianglemeshes. Thesize of these representations imposes limits on applications for which complex 3D models must be acces...
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Most systems that support visual interaction with 3D models use shape representations based on trianglemeshes. The
size of these representations imposes limits on applications for which complex 3D models must be accessed remotely. Techniques for
simplifying and compressing 3D models reduce the transmission time. Multiresolution formats provide quick access to a crude model
and then refine it progressively. Unfortunately, compared to the best nonprogressive compression methods, previously proposed
progressive refinement techniques impose a significant overhead when the full resolution model must be downloaded. The CPM
(Compressed Progressive meshes) approach proposed here eliminates this overhead. It uses a new technique, which refines the
topology of the mesh in batches, which each increase the number of vertices by up to 50 percent. Less than an amortized total of 4 bits
per triangle encode where and how the topological refinements should be applied. We estimate the position of new vertices from the
positions of their topological neighbors in the less refined mesh using a new estimator that leads to representations of vertex
coordinates that are 50 percent more compact than previously reported progressive geometry compression techniques.
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