arrow
Return

Efficient Inter-View Motion Vector Prediction in Multi-View HEVC

delete2018-09-01
delete6
PRE
AI
J
Jae-Yung Lee
J
Jong-Ki Han *
J
Jae‐Gon Kim
T
Truong Q. Nguyen
DOI:10.1109/TBC.2017.2781127delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
When multi-view video sequences are encoded, the efficient motion vector prediction (MVP) is one of the most important techniques to increase the coding performance. The predictive MV should be highly correlated with the actual MV of the current block to be encoded. In this paper, we explain the inefficiency of the MVP algorithm in the multi-view high efficiency video codec (MV-HEVC) standard. In order to solve the inefficiency problem, we propose an enhanced advanced motion vector prediction algorithm in which the geometry interrelation between two neighboring views is derived based on epipolar geometry, similarity transform, and affine transform, and then predicted motion vectors (PMVs) for efficient MV coding are generated using obtained geometry relation. The experiment results show that the proposed scheme outperforms conventional MV-HEVC with a 1.32%-1.19% coding gain because it provides more efficient PMVs than conventional algorithms.
Keywords:
HEVC
MV-HEVC
motion vector predictor
AMVP
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Broadcasting cover
IEEE Transactions on Broadcasting
IF:
4.8
Papers:
2.1K
Citations:
3.0K

Organization

S
Sejong University
Scholars:
8.3K
Papers: 1.1W
Citations: 1.5W
K
Korea Aerospace University
Scholars:
1.1K
Papers: 1.0K
Citations: 513
University of California System cover
University of California System
Scholars:
37.5W
Papers: 33.7W
Citations: 6.6K
researcher View more organizations