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公开(公告)号：US20240282013A1
公开(公告)日：2024-08-22
申请号：US18571361
申请日：2022-06-20
Applicant: InterDigital Patent Holdings, Inc.
Inventor： Jiahao PANG , Dong TIAN , Maurice QUACH , Giuseppe VALENZISE , Frederic DUFAUX
CPC classification number: G06T9/002 , G06T17/00 , G06T2210/56
Abstract: In one implementation, we propose the UnfoldingOperator, which unfolds/flattens an unorganized input 3D point cloud onto a regular 2D grid. Given an input point cloud, an input 2D grid and the reconstructed point cloud produced by the FoldingNet, our proposal maps the input point cloud onto the 2D grid based on the reconstructed point cloud, leading to a 3-channel image. Alternatively, instead of using an image alone to represent a point cloud, the point cloud is decomposed into a codeword and a 3-channel residual image. This residual image is obtained by subtracting the reconstructed point cloud from the original input. The proposed UnfoldingOperator can be applied to point cloud compression, leading to a corresponding compression system that we call UnfoldingCompression. The UnfoldingCompression can work with the TearingCompression, where we can adaptively choose whether to use the UnfoldingCompression or TearingCompression.
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公开(公告)号：US20250014228A1
公开(公告)日：2025-01-09
申请号：US18706208
申请日：2022-10-18
Applicant: InterDigital Patent Holdings, Inc.
Inventor： Maurice QUACH , Jiahao PANG , Muhammad Asad LODHI , Dong TIAN , Giuseppe VALENZISE , Frederic DUFAUX
IPC: G06T9/00
Abstract: In one implementation, we improve the binary voxel-based octree coding method, via a proposed state summarization module for context modeling. Given a current voxel to be encoded or decoded, instead of directly estimating its occupancy probability based on the associated binary occupancy context, a proposed state summarization module is applied to convert the original binary context to a summarized representation. Under the summarized representation, the estimation of the occupancy probability becomes more affordable and effective. In particular, density-based state summarization, pattern-based, learning-based state summarization, and learning-based state summarization methods are provided.
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公开(公告)号：US20240193819A1
公开(公告)日：2024-06-13
申请号：US18556401
申请日：2022-04-29
Applicant: InterDigital Patent Holdings, Inc.
Inventor： Dong TIAN , Jiahao PANG , Maurice QUACH , Giuseppe VALENZISE , Frederic DUFAUX
CPC classification number: G06T9/002 , G06T17/00 , G06T2210/56
Abstract: In one implementation, a learnable transformation TearingTransform over 3D point cloud data is proposed. The TearingTransform could decompose point clouds into two channels: a low rank channel and a sparse channel. The low rank channel corresponds to a codeword representing a rough shape of a point cloud. The sparse channel appears as an image-like data representing residual information that can refine the reconstructed point locations. In an encoder based on TearingTransform, a PN module is used to generate the codeword from the input point cloud; a FN module is used to reconstruct a preliminary point cloud from the codeword and an initial grid image; and a TN module modifies the initial grid image to generate an adjusted grid image. The codeword and the adjusted grid image are compressed. At the decoder, the point cloud can be reconstructed based on the decompressed codeword and adjusted grid image.
