NO-REFERENCE VIDEO QUALITY MEASUREMENT WITH SUPPORT VECTOR REGRESSION

被引：13
|
作者：
Lian, Huicheng [1 ]
机构：
[1] Shanghai Univ, Sch Comp Engn & Sci, Shanghai 200072, Peoples R China
来源：
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS | 2009年 / 19卷 / 06期
关键词：
No-reference video quality measurement; support vector regression; linear regression; video quality; EXTREME LEARNING-MACHINE;
D O I：
10.1142/S0129065709002154
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel approach for no-reference video quality measurement is proposed in this paper. Firstly, various feature extraction methods are used to quantify the quality of videos. Then, a support vector regression model is trained and adopted to predict unseen samples. Six different regression models are compared with the support vector regression model. The experimental results indicate that the combination of different video quality features with a support vector regression model can outperform other methods for no-reference video quality measurement significantly.
引用
收藏
页码：457 / 464
页数：8
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