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Towards robustness and generalization of point cloud representation:A geometry coding method and a large-scale object-level dataset

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Computational Visual Media 2024年第1期10卷 27-43页

作者： Mingye Xu Zhipeng Zhou Yali Wang Yu Qiao Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518000China University of Chinese Academy of Sciences Beijing065001China Shanghai AI Laboratory Shanghai200001China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for SocietyShenzhen518000China Alibaba DAMO Academy Hangzhou242332China

Robustness and generalization are two challenging problems for learning point cloud *** tackle these problems,we first design a novel geometry coding model,which can effectively use an invariant eigengraph to group points with similar geometric information,even when such points are far from each *** also introduce a large-scale point cloud dataset,*** consists of 184 categories and 51,915 synthetic objects,which brings new challenges for point cloud classification,and provides a new benchmark to assess point cloud cross-domain ***,we perform extensive experiments on point cloud classification,using ModelNet40,ScanObjectNN,and our PCNet184,and segmentation,using ShapeNetPart and *** method achieves comparable performance to state-of-the-art methods on these datasets,for both supervised and unsupervised *** and our dataset are available at https://***/MingyeXu/PCNet184.

关键词： geometry coding self-supervised learning point cloud classification segmentation 3D analysis

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Local geometry-Based Intra Prediction for Octree-Structured geometry coding of Point Clouds

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2023年第2期33卷 886-896页

作者： Wang, Zhecheng Wan, Shuai Wei, Lei Northwestern Polytech Univ Sch Elect & Informat Xian 710129 Peoples R China RMIT Univ Sch Engn Melbourne Vic 3001 Australia

Point cloud compression (PCC) is crucial for efficient and flexible storage as well as feasible transmission of point clouds in practice. For geometry compression, one popular approach is the octree-based solution. The intra prediction mechanism utilizes the spatial correlation in the static point cloud to predict the occupancy bit of the octree node for entropy coding, reducing the spatial redundancy. In this study, two local geometry-based prediction methods are proposed following statistical and theoretical analyses: binary prediction, which outputs the binary state (i.e., occupied or unoccupied), and ternary prediction, which provides a third option other than occupied or unoccupied (i.e., not predicted). In comparison to the state-of-the-art, the proposed binary prediction offers the Bjontegaard delta rate (BD-rate) of -0.8% for lossy compression and the bits per input point (bpip) of 100.09% for lossless compression in average, respectively. The binary prediction reduces the computational complexity in terms of more than 20% decrease in decoding time. In particular, it also provides noticeable reduction of the memory usage during entropy coding. The proposed ternary prediction provides -1.2% BD-rate for lossy compression and 97.19% bpip for lossless compression in average, respectively, in comparison to the state-of-the-art. While achieving performance gain, it is considerably more computational efficient by saving about 18% decoding time. Due to these advantages, part of the proposed ternary prediction has been adopted by the ongoing MPEG standard of geometry-based point cloud compression (G-PCC).

关键词： Point cloud compression Encoding geometry Octrees Correlation Three-dimensional displays Euclidean distance geometry coding octree structure intra prediction

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Wavelet-Based geometry coding for 3D Mesh Using Space Frequency Quantization

Wavelet-Based Geometry Coding for 3D Mesh Using Space Freque...

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12th World Multi-Conference on Systemics, Cybernetics and Informatics/14th International Conference on Information Systems Analysis and Synthesis

作者： El-Lithey, S. T. Sheta, W. M. Doma, S. B. Informat Res Inst Alexandria Egypt Sinai Univ Fac Informat Technol & Comp Sci Al Arish Egypt

ISBN: (纸本)9781934272350

In this paper, a pure geometry compression algorithm for 3D semi-regular meshes, based on wavelet transform and space frequency quantization for 3D meshes, has been introduced. The local frame was applied to wavelet coefficients to be more independent, and the 3D SFQ was used to quantize the coefficients. The proposed algorithm was compared with the zero-tree coder for MAPS meshes. The rate-distortion curves results are significantly better than those for zero-tree coder in the high rates.

关键词： Mesh compression polygonal meshes geometry coding wavelets space frequency quantization

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Progressive geometry coding of partitioned 3D models

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2003年第11期E86D卷 2418-2425页

作者： Okuda, M Takahashi, S Univ Kitakyushu Kitakyushu Fukuoka 8080135 Japan

Files of 3D mesh models are often large and hence time-consuming to retrieve from a storage device or to download through the network. Most 3D viewing applications need to obtain the entire file of a 3D model in order to display the model, even when the user is interested only in a small part, or a low-resolution version, of the model. Therefore, coding that enables multiresolution and ROI (Region Of Interest) transmission of 3D models is desired. In this paper, we propose a coding algorithm of 3D models based on partitioning schemes. The algorithm actually partitions the 3D meshes into some small submeshes according to some geometric criteria (such as curvatures), and then codes each small sub-meshes separately to transmit it progressively to users on demand. The key idea of this paper lies in the mesh partitioning procedure prior to its LOD control, which enables good compression ratio of the mesh data as well as some other good capable properties through network transmission such as ROI coding, view-adaptive transmission, error resilient coding, etc.

关键词： 3D models geometry coding model partitioning compression

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POINT CLOUD geometry SCALABLE coding WITH A QUALITY-CONDITIONED LATENTS PROBABILITY ESTIMATOR 31

POINT CLOUD GEOMETRY SCALABLE CODING WITH A QUALITY-CONDITIO...

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2024 International Conference on Image Processing

作者： Mari, Daniele Guarda, Andre F. R. Rodrigues, Nuno M. M. Milani, Simone Pereira, Fernando Univ Padua Padua Italy Univ Lisbon Inst Super Tecn Lisbon Portugal Politecn Leiria ESTG Leiria Portugal Inst Telecomunicacoes Lisbon Portugal

ISBN: (纸本)9798350349405;9798350349399

The widespread usage of point clouds (PC) for immersive visual applications has resulted in the use of very heterogeneous receiving conditions and devices, notably in terms of network, hardware, and display capabilities. In this scenario, quality scalability, i.e., the ability to reconstruct a signal at different qualities by progressively decoding a single bitstream, is a major requirement that has yet to be conveniently addressed, notably in most learning-based PC coding solutions. This paper proposes a quality scalability scheme, named Scalable Quality Hyperprior (SQH), adaptable to learning-based static point cloud geometry codecs, which uses a Quality-conditioned Latents Probability Estimator (QuLPE) to decode a high-quality version of a PC learning-based representation, based on an available lower quality base layer. SQH is integrated in the future JPEG PC coding standard, allowing to create a layered bitstream that can be used to progressively decode the PC geometry with increasing quality and fidelity. Experimental results show that SQH offers the quality scalability feature with very limited or no compression performance penalty at all when compared with the corresponding non-scalable solution, thus preserving the significant compression gains over other state-of-the-art PC codecs.

关键词： Point cloud coding scalable coding geometry coding deep learning JPEG PCC standard

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Multi-view coding for Image-Based Rendering using 3-D scene geometry

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2003年第11期13卷 1092-1106页

作者： Magnor, M Ramanathan, P Girod, B Max Planck Inst Informat D-66123 Saarbrucken Germany Stanford Univ Stanford CA 94305 USA

To store and transmit the large, amount of image data necessary for Image-based Rendering (IBR), efficient coding schemes are required. This paper presents two different approaches which exploit three-dimensional scene geometry for multi-view compression. In texture-based coding, images are converted to view-dependent texture maps for compression. In model-aided predictive coding, scene geometry is used for disparity compensation and occlusion detection between images. While both coding strategies are able to attain compression ratios exceeding 2000:1, individual coding performance is found to depend on the accuracy of the available geometry model. Experiments with real-world as well as synthetic image sets show that texture-based coding is more sensitive to geometry inaccuracies than predictive coding. A rate-distortion theoretical analysis of both schemes supports these findings. For reconstructed approximate geometry models, model-aided predictive coding performs best, while texture-based coding yields superior coding results if scene geometry is exactly known.

关键词： geometry coding image-based rendering (IBR) light field compression model-based coding multi-view coding analysis multi-view compression

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Mean square error approximation for wavelet-based semiregular mesh compression

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2006年第4期12卷 649-657页

作者： Payan, F Antonini, M Univ Nice Sophia Antipolis CNRS UMR 6070 Lab 13S F-06903 Sophia Antipolis France

The objective of this paper is to propose an efficient model-based bit allocation process optimizing the performances of a wavelet coder for semiregular meshes. More precisely, this process should compute the best quantizers for the wavelet coefficient subbands that minimize the reconstructed mean square error for one specific target bitrate. In order to design a fast and low complex allocation process, we propose an approximation of the reconstructed mean square error relative to the coding of semiregular mesh geometry. This error is expressed directly from the quantization errors of each coefficient subband. For that purpose, we have to take into account the influence of the wavelet filters on the quantized coefficients. Furthermore, we propose a specific approximation for wavelet transforms based on lifting schemes. Experimentally, we show that, in comparison with a "naive" approximation ( depending on the subband levels), using the proposed approximation as distortion criterion during the model-based allocation process improves the performances of a wavelet-based coder for any model, any bitrate, and any lifting scheme.

关键词： weighted mean square error (MSE) biorthogonal wavelet lifting scheme butterfly scheme bit allocation geometry coding semiregular meshes

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Adaptive coding of generic 3D triangular meshes based on octree decomposition

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VISUAL COMPUTER 2012年第6-8期28卷 819-827页

作者： Tian, Jiang Jiang, Wenfei Luo, Tao Cai, Kangying Peng, Jingliang Wang, Wencheng Technicolor Res & Innovat Beijing Peoples R China ISCAS State Key Lab Comp Sci Beijing Peoples R China Shandong Univ Jinan 250100 Shandong Peoples R China

In this paper, we present an adaptive-coding method for generic triangular meshes including both regular and irregular meshes. Though it is also based on iterative octree decomposition of the object space for the original mesh, as some prior arts, it has novelties in the following two aspects. First, it mathematically models the occupancy codes containing only a single-"1" bit for accurate initialization of the arithmetic coder at each octree level. Second, it adaptively prioritizes the bits in an occupancy code using a local surface smoothness measure that is based on triangle areas and therefore mitigates the effect of non-uniform vertex sampling over the surface. As a result, the proposed 3D mesh coder yields outstanding coding performance for both regular and irregular meshes and especially for the latter, as demonstrated by the experiments.

关键词： Octree decomposition Irregular mesh Mesh compression geometry coding

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An efficient bit allocation for compressing normal meshes with an error-driven quantization

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COMPUTER AIDED GEOMETRIC DESIGN 2005年第5期22卷 466-486页

作者： Payan, F Antonini, M Univ Nice Sophia Antipolis CNRS UMR 6070 Lab I3S F-06903 Sophia Antipolis France

We propose a new wavelet compression algorithm based on the rate-distortion optimization for densely sampled triangular meshes. Exploiting the normal remesher of Guskov et al., the proposed algorithm includes a wavelet transform and an original bit allocation optimizing the quantization of the wavelet coefficients. The allocation process minimizes the reconstruction error for a given bit budget. As distortion measure, we use the mean square error of the normal mesh quantization, expressed according to the quantization error of each subband. We show that this metric is a suitable criterion to evaluate the reconstruction error, i.e., the geometric distance between the input mesh and the quantized normal one. Moreover, to design a fast bit allocation, we propose a model-based approach, depending on distribution of the wavelet coefficients. Compared to the state-of-the-art methods for normal meshes, our algorithm provides improvements in coding performance, up to +2.5 dB compared to the original zerotree coder. (C) 2005 Elsevier B.V. All rights reserved.

关键词： shape compression geometry coding normal meshes model-based bit allocation wavelet transform rate-distortion optimization multiresolution analysis

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Adaptive geometry Partition for Point Cloud Compression

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2021年第12期31卷 4561-4574页

作者： Zhang, Xiang Gao, Wen Tencent Amer Media Lab Palo Alto CA 94306 USA

Octree (OT) geometry partitioning has been acknowledged as an efficient representation in state-of-the-art point cloud compression (PCC) schemes. In this work, an adaptive geometry partition and coding scheme is proposed to improve the OT based coding framework. First, quad-tree (QT) and binary-tree (BT) partitions are introduced as alternative geometry partition modes for the first time under the context of OT-based point cloud compression. The adaptive geometry partition scheme enables flexible three-dimensional (3D) space representations and higher coding efficiency. However, exhaustive searching for the optimal partition from all possible combinations of OT, QT and BT is impractical because the entire search space could be huge. Therefore, two hyper-parameters are introduced to specify the conditions on which QT and BT partitions will be applied. Once the two parameters are determined, the partition mode can be derived according to the geometry shape of current coding node. To investigate the impact of different partition combinations on the coding gains, we conduct thorough mathematical and experimental analyses. Based on the analyses, an adaptive parameter selection scheme is presented to optimize the coding efficiency adaptively, where multi-resolution features are extracted from the partition pyramid and a decision tree model is trained for the optimal hyper-parameters. The proposed adaptive geometry partition scheme has shown significant coding gains, and it has been adopted in the state-of-the-art MPEG geometry based PCC (G-PCC) standard. For the sparser point clouds, the bit savings are up to 10.8% and 3.5% for lossy and lossless geometry coding without significant complexity increment.

关键词： Encoding geometry Three-dimensional displays Standards Transform coding Video coding Image coding Point cloud compression geometry coding octree partition quad-tree partition binary-tree partition

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