Paper Info
Title
Pattern based video coding with uncovered background
Abstract
1The pattern-based video coding (PVC) outperforms the H.264 through better exploitation of block partitioning and partial block skipping. In the PVC scheme the best pattern is determined against the moving regions (MRs) in a macroblock (MB) of the current frame against the co-located MB in the reference frame; motion estimation (ME) and motion compensation (MC) are carried out using the pattern covered MRs, and the rest of the regions are treated as skipped areas. The MRs can be due to the object areas and the uncovered background (UCB) areas. Thus, the ME & MC by the pattern for the MRs of the UCB would not be accurate if there is no similar region in the reference frame. As a result no coding gain can be achieved for the UCB. Recently a dynamic background frame termed as the McFIS (the most common frame of a scene) has been generated using Gaussian mixture models for object detection. In this paper we propose a new PVC technique which will use the McFIS as a reference frame to determine the MRs where only object areas will be captured as the MRs. Thus, the proposed technique overcomes the mismatch problem of the UCB for ME&MC. The experimental results confirm the superiority of the proposed scheme in comparison with the existing PVC and McFIS-based methods by achieving significant image quality gain.
Year
DOI
Venue
2010
10.1109/ICIP.2010.5654053
Image Processing
Keywords
Field
DocType
motion estimation,video coding,Gaussian mixture model,image quality,motion compensation,motion estimation,object detection,pattern based video coding,uncovered background,H.264,Video coding,light change,motion estimation,multiple reference frames,pattern based video coding,repetitive motion,uncovered background
Macroblock,Reference frame,Object detection,Computer vision,Coding gain,Pattern recognition,Computer science,Motion compensation,Image quality,Artificial intelligence,Motion estimation,Pattern matching
Conference
ISSN
ISBN
Citations 
1522-4880 E-ISBN : 978-1-4244-7993-1
978-1-4244-7993-1
2
PageRank 
References 
Authors
0.36
9
4
Name
Order
Citations
PageRank
Manoranjan Paul137286.59
Weisi Lin25366280.14
Chiew Tong Lau340635.82
Bu-Sung Lee42119140.18