MACHINE LEARNING BASED MODELING OF SPATIAL AND TEMPORAL FACTORS FOR VIDEO QUALITY ASSESSMENT

被引：0
|
作者：
Narwaria, Manish [1 ]
Lin, Weisi [1 ]
机构：
[1] Nanyang Technol Univ, Sch Comp Engn, Singapore, Singapore
来源：
2011 18TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2011年
关键词：
Video quality assessment (VQA); machine learning; spatial quality; temporal quality;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Unlike image quality, video quality is affected by the temporal factor, in addition to the spatial one. In this paper, we investigate into the impact of both the factors on the overall perceived video quality and combine them into a metric. We use machine learning as a tool to study and analyze the relationship between the factors and the overall perceived video quality. It is shown that apart from their individual contributions, the interaction of the two factors also plays a role in determining the overall video quality. We report the experimental results and the related analysis using videos from two publicly available databases.
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页数：4
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