CLC number: TN919.8
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
Cited: 4
Clicked: 5521
Liu Yu-xin, Kurceren Ragip, Budhia Udit. Video classification for video quality prediction[J]. Journal of Zhejiang University Science A, 2006, 7(5): 919-926.
@article{title="Video classification for video quality prediction",
author="Liu Yu-xin, Kurceren Ragip, Budhia Udit",
journal="Journal of Zhejiang University Science A",
volume="7",
number="5",
pages="919-926",
year="2006",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.A0919"
}
%0 Journal Article
%T Video classification for video quality prediction
%A Liu Yu-xin
%A Kurceren Ragip
%A Budhia Udit
%J Journal of Zhejiang University SCIENCE A
%V 7
%N 5
%P 919-926
%@ 1673-565X
%D 2006
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.A0919
TY - JOUR
T1 - Video classification for video quality prediction
A1 - Liu Yu-xin
A1 - Kurceren Ragip
A1 - Budhia Udit
J0 - Journal of Zhejiang University Science A
VL - 7
IS - 5
SP - 919
EP - 926
%@ 1673-565X
Y1 - 2006
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2006.A0919
Abstract: In this paper we propose a novel method for video quality prediction using video classification. In essence, our approach can serve two goals: (1) To measure the video quality of compressed video sequences without referencing to the original uncompressed videos, i.e., to realize no-Reference (NR) video quality evaluation; (2) To predict quality scores for uncompressed video sequences at various bitrates without actually encoding them. The use of our approach can help realize video streaming with ideal quality of Service (QoS). Our approach is a low complexity solution, which is specially suitable for application to mobile video streaming where the resources at the handsets are scarce.
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