Joint Texture and Depth Coding using Cuboid Data Compression

Manoranjan Paul, Subrata Chakraborty, Manzur Murshed, Pallab Podder

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

Abstract

The latest multiview video coding (MVC) standards such as 3D-HEVC and H.264/MVC normally encodes texture and depth videos separately. Significant amount of rate-distortion performance and computational performance are sacrificed due to separate encoding due to the lack of exploitation of joint information. Obviously, separate encoding also creates synchronization issue for 3D scene formation in the decoder. Moreover, the hierarchical frame referencing architecture in the MVC creates random access frame delay. In this paper we develop an encoder and decoder framework where we can encode texture and depth video jointly by forming and encoding 3D cuboid using high dimensional entropy coding. The results from our experiments show that our proposed framework outperforms the 3D-HEVC in rate-distortion performance and reduces the computational time significantly by reducing random access frame delay.
Original languageEnglish
Title of host publicationProceedings of the 18th International Conference on Computer and Information Technology
Subtitle of host publicationICCIT 2015
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages138-143
Number of pages6
ISBN (Electronic)9781467399302
DOIs
Publication statusPublished - 2015
Event18th International Conference on Computer and Information Technology: ICCIT 2015 - Military Institute of Science and Technology (MIST), Dhaka, Bangladesh
Duration: 21 Dec 201523 Dec 2015

Conference

Conference18th International Conference on Computer and Information Technology
Country/TerritoryBangladesh
CityDhaka
Period21/12/1523/12/15

Fingerprint

Dive into the research topics of 'Joint Texture and Depth Coding using Cuboid Data Compression'. Together they form a unique fingerprint.

Cite this