Results 21 to 30 of about 44,716 (282)
Contextual Homogeneity-Based Patch Decomposition Method for Higher Point Cloud Compression
IEEE Access, 2020 Point cloud content is widely used to store and represent 3D volumetric objects with a complex and detailed representation from any direction of view.
Sungryeul Rhyu +3 more
doaj +1 more source
Lossless Compression of Point Cloud Sequences Using Sequence Optimized CNN Models
IEEE Access, 2022 In this paper we propose a new paradigm for encoding the geometry of dense point cloud sequences, where a convolutional neural network (CNN), which estimates the encoding distributions, is optimized on several frames of the sequence to be compressed.
Emre C. Kaya, Ioan Tabus
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Efficient Quadtree Search for HEVC Coding Units for V-PCC
IEEE Access, 2021 Dynamic point clouds (DPC) are new media storage formats that allow end-users to watch objects/scenes in a three-dimensional (3D) sense. It can be displayed from different angles throughout time.
Ting-Lan Lin +7 more
doaj +1 more source
A dynamical model for the dusty ring in the Coalsack [PDF]
, 2006 Lada et al. recently presented a detailed near-infrared extinction map of Globule G2 in the Coalsack molecular cloud complex, showing that this starless core has a well-defined central extinction minimum.
A. P. Whitworth +24 more
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Joint Geometry and Color Projection-Based Point Cloud Quality Metric
IEEE Access, 2022 Point cloud coding solutions have been recently standardized to address the needs of multiple application scenarios. The design and assessment of point cloud coding methods require reliable objective quality metrics to evaluate the level of degradation ...
Alireza Javaheri +3 more
doaj +1 more source
The ring compression test: Analysis of dimensions and canonical geometry [PDF]
, 2015 The compression ring test is universally accepted as a perfectly valid method by which determine simply and reliably the adhesion friction factor in a plastic deformation process.
Martín-Fernández, Francisco de Sales
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3D Point Cloud Attribute Compression Using Geometry-Guided Sparse Representation
IEEE Transactions on Image Processing, 2020 3D point clouds associated with attributes are considered as a promising paradigm for immersive communication. However, the corresponding compression schemes for this media are still in the infant stage. Moreover, in contrast to conventional image/video compression, it is a more challenging task to compress 3D point cloud data, arising from the ...
Shuai Gu +4 more
openaire +4 more sources
Learned Point Cloud Geometry Compression
, 2019 This paper presents a novel end-to-end Learned Point Cloud Geometry Compression (a.k.a., Learned-PCGC) framework, to efficiently compress the point cloud geometry (PCG) using deep neural networks (DNN) based variational autoencoders (VAE). In our approach, PCG is first voxelized, scaled and partitioned into non-overlapped 3D cubes, which is then fed ...
Wang, Jianqiang +5 more
openaire +2 more sources
LVAC: Learned volumetric attribute compression for point clouds using coordinate based networks
Frontiers in Signal Processing, 2022 We consider the attributes of a point cloud as samples of a vector-valued volumetric function at discrete positions. To compress the attributes given the positions, we compress the parameters of the volumetric function.
Berivan Isik +4 more
doaj +1 more source
A System for Acquiring, Processing, and Rendering Panoramic Light Field Stills for Virtual Reality
, 2018 We present a system for acquiring, processing, and rendering panoramic light field still photography for display in Virtual Reality (VR). We acquire spherical light field datasets with two novel light field camera rigs designed for portable and efficient
Debevec, Paul +4 more
core +1 more source