JOURNAL ARTICLE

Content Based Video Quality Estimation for H.264/AVC Video Streaming

Abstract

The scope of this work is the estimation of video quality for low resolution video sequences typical in (mobile) video streaming applications. Since the video quality experienced by users depends considerably on the spatial (edges, colors, ...) and temporal (movement speed, direction, ...) features of the video sequence, this paper presents a two-step approach to quality estimation. Firstly, shots between two scene changes are analyzed and their content class is found. Secondly, based on the content class, frame rate and bitrate, an estimation of quality is carried out. In this paper, the design of the content classifier as well as an appropriate choice of the content classes and their characteristics is discussed. Moreover, the design of quality metric is presented, based on the mean opinion score obtained by a survey. The performance of the proposed method is evaluated and compared to several common methods. The results show that the proposed approach provides powerful means of estimating the video quality experienced by users for low resolution video streaming services.

Keywords:
Computer science PEVQ Video quality Subjective video quality Video tracking Video compression picture types Computer vision Video processing Artificial intelligence Mean opinion score Frame (networking) Quality (philosophy) Metric (unit) Image quality Image (mathematics) Telecommunications

Metrics

54
Cited By
4.80
FWCI (Field Weighted Citation Impact)
20
Refs
0.95
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image and Video Quality Assessment
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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