- Title
- A novel depth motion vector coding exploiting spatial and inter-component clustering tendency
- Creator
- Shahriyar, Shampa; Murshed, Manzur; Ali, Mortuza; Paul, Manoranjan
- Date
- 2015
- Type
- Text; Conference proceedings; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/102238
- Identifier
- vital:10775
- Identifier
-
https://doi.org/10.1109/VCIP.2015.7457774
- Identifier
- ISBN:9781467373142 (ISBN)
- Abstract
- Motion vectors of depth-maps in multiview and free-viewpoint videos exhibit strong spatial as well as inter-component clustering tendency. This paper presents a novel coding technique that first compresses the multidimensional bitmaps of macroblock mode and then encodes only the non-zero components of motion vectors. The bitmaps are partitioned into disjoint cuboids using binary tree based decomposition so that the 0's and 1's are either highly polarized or further sub-partitioning is unlikely to achieve any compression. Each cuboid is entropy-coded as a unit using binary arithmetic coding. This technique is capable of exploiting the spatial and inter-component correlations efficiently without the restriction of scanning the bitmap in any specific linear order as needed by run-length coding. As encoding of non-zero component values no longer requires denoting the zero value, further compression efficiency is achieved. Experimental results on standard multiview test video sequences have comprehensively demonstrated the superiority of the proposed technique, achieving overall coding gain against the state-of-the-art in the range [22%, 54%] and on average 38%. © 2015 IEEE.; 2015 Visual Communications and Image Processing, VCIP 2015
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Relation
- Visual Communications and Image Processing, VCIP 2015; Singapore; 13th-16th December 2015 p. 1-4; http://purl.org/au-research/grants/arc/DP130103670
- Rights
- Copyright © 2015 IEEE.
- Rights
- This metadata is freely available under a CCO license
- Subject
- Binary tree based decomposition; Binary trees; Correlation; Cuboid Coding; Data compression; Depth Coding; Encoding; Motion Vector Coding; Multiview; Videos
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