Joint texture and depth coding using cuboid data compression

Paul, Manoranjan and Chakraborty, Subrata and Murshed, Manzur and Podder, Pallab Kanti (2015) Joint texture and depth coding using cuboid data compression. In: IEEE 18th International Conference on Computer and Information Technology, 21-23 Dec 2015, Dhaka, Bangladesh.

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.


Statistics for USQ ePrint 28089
Statistics for this ePrint Item
Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Files associated with this item cannot be displayed due to copyright restrictions.
Faculty / Department / School: Current - Faculty of Business, Education, Law and Arts - School of Management and Enterprise
Date Deposited: 02 Feb 2016 23:52
Last Modified: 05 Jul 2016 03:41
Uncontrolled Keywords: video coding; cuboid; McFIS; dynamic background; mutiview video
Fields of Research : 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
URI: http://eprints.usq.edu.au/id/eprint/28089

Actions (login required)

View Item Archive Repository Staff Only