Silhouette 4D With Context Selection: Lossless Geometry Compression of Dynamic Point Clouds

Recently we have proposed a coding algorithm of point cloud geometry based on a rather different approach from the popular octree representation. In our algorithm, the point cloud is decomposed in silhouettes, hence the name Silhouette Coder, and context adaptive arithmetic coding is used to exploit...

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Published in:IEEE signal processing letters Vol. 28; pp. 1660 - 1664
Main Authors: Ramalho, Evaristo, Peixoto, Eduardo, Medeiros, Edil
Format: Journal Article
Language:English
Published: New York IEEE 2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Arithmetic coding
Codecs
Coders
Context
Encoding
Geometry
Image coding
Image compression
inter coder
lossless coding
Octrees
Point clouds
Signal processing algorithms
Three-dimensional displays
Transform coding
ISSN:1070-9908, 1558-2361
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Abstract Recently we have proposed a coding algorithm of point cloud geometry based on a rather different approach from the popular octree representation. In our algorithm, the point cloud is decomposed in silhouettes, hence the name Silhouette Coder, and context adaptive arithmetic coding is used to exploit redundancies within the point cloud (intra frame coding), and also using a reference point cloud (inter frame coding). In this letter we build on our previous work and propose a context selection algorithm as a pre-processing stage. With this algorithm, the point cloud is first parsed testing a large number of candidate context locations. The algorithm selects a small number of these contexts that better reflect the current point cloud, and then encode it with this choice. The proposed method further improves the results of our previous coder, Silhouette 4D, by <inline-formula><tex-math notation="LaTeX">10 \%</tex-math></inline-formula>, on average, on a dynamic point cloud dataset of the JPEG Pleno, and achieves bitrates competitive with some high quality lossy coders such as the MPEG G-PCC.
AbstractList Recently we have proposed a coding algorithm of point cloud geometry based on a rather different approach from the popular octree representation. In our algorithm, the point cloud is decomposed in silhouettes, hence the name Silhouette Coder, and context adaptive arithmetic coding is used to exploit redundancies within the point cloud (intra frame coding), and also using a reference point cloud (inter frame coding). In this letter we build on our previous work and propose a context selection algorithm as a pre-processing stage. With this algorithm, the point cloud is first parsed testing a large number of candidate context locations. The algorithm selects a small number of these contexts that better reflect the current point cloud, and then encode it with this choice. The proposed method further improves the results of our previous coder, Silhouette 4D, by [Formula Omitted], on average, on a dynamic point cloud dataset of the JPEG Pleno, and achieves bitrates competitive with some high quality lossy coders such as the MPEG G-PCC.
Recently we have proposed a coding algorithm of point cloud geometry based on a rather different approach from the popular octree representation. In our algorithm, the point cloud is decomposed in silhouettes, hence the name Silhouette Coder, and context adaptive arithmetic coding is used to exploit redundancies within the point cloud (intra frame coding), and also using a reference point cloud (inter frame coding). In this letter we build on our previous work and propose a context selection algorithm as a pre-processing stage. With this algorithm, the point cloud is first parsed testing a large number of candidate context locations. The algorithm selects a small number of these contexts that better reflect the current point cloud, and then encode it with this choice. The proposed method further improves the results of our previous coder, Silhouette 4D, by <inline-formula><tex-math notation="LaTeX">10 \%</tex-math></inline-formula>, on average, on a dynamic point cloud dataset of the JPEG Pleno, and achieves bitrates competitive with some high quality lossy coders such as the MPEG G-PCC.
Author Ramalho, Evaristo
Peixoto, Eduardo
Medeiros, Edil
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SubjectTerms Algorithms
Arithmetic coding
Codecs
Coders
Context
Encoding
Geometry
Image coding
Image compression
inter coder
lossless coding
Octrees
Point clouds
Signal processing algorithms
Three-dimensional displays
Transform coding
Title Silhouette 4D With Context Selection: Lossless Geometry Compression of Dynamic Point Clouds
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Volume 28
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