2006Journal of Zhejiang University. Science ARequires access

Video classification for video quality prediction

Yu‐xin Liu, Ragip Kurceren, Udit Budhia

Open publisher page 16 citations

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.

About this research paper

What this paper is about

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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OpenAlex reports 16 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available 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.

Key concepts: Uncompressed video, Computer science, Video quality, Subjective video quality, Video compression picture types, Video processing, Quality (philosophy), Quality of service

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