Name
Title | ||
|---|---|---|
Efficient Motion Re-Estimation Method Based On K-Means Clustering For Spatial Resolution Reduction Transcoding |
Abstract | ||
|---|---|---|
In this paper, we present a spatial resolution reduction transcoding architecture for H.264/AVC with a low-complexity compensation technique. A fast motion vector re-estimation based on a k-means clustering algorithm is proposed for efficiently determining a motion vector and a reference frame. A motion vector refinement technique is used to further improve the rate-distortion performance without additional high complexity. The proposed method significantly reduces the motion vector estimation complexity up to 10 times while the loss of rate distortion performance is negligible with a decrease of 0.1dB in BD-PSNR and 3% increase in the BD-RATE. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/PCS.2012.6213332 | 2012 PICTURE CODING SYMPOSIUM (PCS) |
Keywords | Field | DocType |
motion estimation,k means clustering algorithm,spatial resolution,estimation,k means clustering,decoding,video transcoding,reference frame,vectors,transcoding | Reference frame,Computer vision,Transcoding,Block-matching algorithm,Quarter-pixel motion,Computer science,Motion compensation,Theoretical computer science,Artificial intelligence,Motion estimation,Cluster analysis,Motion vector | Conference |
Citations | PageRank | References |
2 | 0.45 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kyoung-Hwan Kim | 1 | 7 | 1.60 |
| Soongi Hong | 2 | 3 | 2.09 |
| Yoonsik Choe | 3 | 91 | 28.68 |