Subjective and Objective Testing in Support of the JPEG Pleno Point Cloud Compression Activity

Perry, S; Da Silva Cruz, LA; Prazeres, J; Pinheiro, A; Dumic, E; Lazzarotto, D; Ebrahimi, T

Subjective and Objective Testing in Support of the JPEG Pleno Point Cloud Compression Activity

Perry, S

Da Silva Cruz, LA Prazeres, J Pinheiro, A Dumic, E Lazzarotto, D Ebrahimi, T

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Publisher:: Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:: Conference Proceeding
Citation:: Proceedings - European Workshop on Visual Information Processing, EUVIP, 2022, 2022-September, pp. 1-6
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Perry, S https://orcid.org/0000-0002-2794-3178
dc.contributor.author	Da Silva Cruz, LA
dc.contributor.author	Prazeres, J
dc.contributor.author	Pinheiro, A
dc.contributor.author	Dumic, E
dc.contributor.author	Lazzarotto, D
dc.contributor.author	Ebrahimi, T
dc.date	2022-09-11
dc.date.accessioned	2023-02-06T06:51:55Z
dc.date.available	2023-02-06T06:51:55Z
dc.date.issued	2022-01-01
dc.identifier.citation	Proceedings - European Workshop on Visual Information Processing, EUVIP, 2022, 2022-September, pp. 1-6
dc.identifier.isbn	9781665466233
dc.identifier.issn	2471-8963
dc.identifier.uri	http://hdl.handle.net/10453/165946
dc.description.abstract	Point clouds have many applications in today's society ranging from entertainment to autonomous driving. With these new applications comes the need to compress the growing volume of point cloud data in a manner that is both suitable for human visualization and machine processing applications. The JPEG Pleno Point Cloud activity has been working toward a learning-based coding standard for point clouds, offering a single-stream, compact compressed domain representation, supporting advanced flexible data access functionalities targeting both in-teractive human visualization, and effective performance for 3D processing and machine-related computer vision tasks. As part of this activity, the JPEG Committee has been performing a number of exploration studies to evaluate existing coding standards as well set up baseline anchors and examine objective metrics against which new learning-based solutions may be compared. This article provides an overview of the JPEG Pleno Point Cloud activity and discusses challenges and solutions to the problem of evaluating and comparing cloud coding solutions. Experimental results will be presented demonstrating methodologies used by the JPEG Committee for point cloud compression assessment as well as outlining the performance of current state of the art compression standards on point clouds as well as the sensitivity of the objective metrics used for this activity to various adjustable parameters.
dc.language	en
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof	Proceedings - European Workshop on Visual Information Processing, EUVIP
dc.relation.ispartof	2022 10th European Workshop on Visual Information Processing (EUVIP)
dc.relation.isbasedon	10.1109/EUVIP53989.2022.9922803
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Subjective and Objective Testing in Support of the JPEG Pleno Point Cloud Compression Activity
dc.type	Conference Proceeding
utslib.citation.volume	2022-September
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	open_access	*
dc.date.updated	2023-02-06T06:51:54Z
pubs.finish-date	2022-09-14
pubs.publication-status	Published
pubs.start-date	2022-09-11
pubs.volume	2022-September

Abstract:

Point clouds have many applications in today's society ranging from entertainment to autonomous driving. With these new applications comes the need to compress the growing volume of point cloud data in a manner that is both suitable for human visualization and machine processing applications. The JPEG Pleno Point Cloud activity has been working toward a learning-based coding standard for point clouds, offering a single-stream, compact compressed domain representation, supporting advanced flexible data access functionalities targeting both in-teractive human visualization, and effective performance for 3D processing and machine-related computer vision tasks. As part of this activity, the JPEG Committee has been performing a number of exploration studies to evaluate existing coding standards as well set up baseline anchors and examine objective metrics against which new learning-based solutions may be compared. This article provides an overview of the JPEG Pleno Point Cloud activity and discusses challenges and solutions to the problem of evaluating and comparing cloud coding solutions. Experimental results will be presented demonstrating methodologies used by the JPEG Committee for point cloud compression assessment as well as outlining the performance of current state of the art compression standards on point clouds as well as the sensitivity of the objective metrics used for this activity to various adjustable parameters.

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http://hdl.handle.net/10453/165946