Dynamic point cloud compression using a cuboid oriented discrete cosine based motion model

Ashek Ahmmed, Manoranjan Paul, Manzur Murshed, David Taubman

Research output: Book chapter/Published conference paperConference paperpeer-review

Abstract

Immersive media representation format based on point clouds has underpinned significant opportunities for extended reality applications. Point cloud in its uncompressed format require very high data rate for storage and transmission. The video based point cloud compression technique projects a dynamic point cloud into geometry and texture video sequences. The projected texture video is then coded using modern video coding standard like HEVC. Since the properties of projected texture video frames are different from traditional video frames, HEVC-based commonality modeling can be inefficient. An improved commonality modeling technique is proposed that employs discrete cosine basis oriented motion models and the domains of such models are approximated by homogeneous regions called cuboids. Experimental results show that the proposed commonality modeling technique can yield savings in bit rate of up to 4.17%.
Original languageEnglish
Title of host publication2021 IEEE International Conference on Acoustics, Speech and Signal Processing
PublisherIEEE
Number of pages5
ISBN (Electronic)9781728176055
ISBN (Print)9781728176062
DOIs
Publication statusPublished - 13 May 2021
Event2021 IEEE International Conference on Acoustics, Speech and Signal Processing - Metro Toronto Convention Centre, Toronto, Canada
Duration: 06 Jun 202111 Jun 2021
https://2021.ieeeicassp.org/default.asp
https://ieeexplore.ieee.org/xpl/conhome/9413349/proceeding (Conference proceedings)

Publication series

Name
PublisherIEEE
ISSN (Print)1520-6149
ISSN (Electronic)2379-190X

Conference

Conference2021 IEEE International Conference on Acoustics, Speech and Signal Processing
Abbreviated titleExtracting Knowledge from Information
Country/TerritoryCanada
CityToronto
Period06/06/2111/06/21
OtherThe international Conference on Acoustics, Speech, & Signal Processing (ICASSP), is the IEEE Signal Processing Society’s flagship conference on signal processing and its applications. The 46th edition of ICASSP will be held in the dynamic city of Toronto, Canada; one of the most multicultural and cosmopolitan cities in the world. The programme will include keynotes by pre-eminent international speakers, cutting-edge tutorial topics, and forward-looking special sessions. ICASSP also provides a great networking opportunity with a wide range of like-minded professionals from academia, industry and government organizations.
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