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Impact of automatic region-of-interest coding on perceived quality in mobile video
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  • 作者:Ivan Himawan ; Wei Song ; Dian Tjondronegoro
  • 关键词:Mobile video quality ; Human vision system ; Video coding ; Subjective quality
  • 刊名:Multimedia Tools and Applications
  • 出版年:2017
  • 出版时间:January 2017
  • 年:2017
  • 卷:76
  • 期:1
  • 页码:785-813
  • 全文大小:
  • 刊物类别:Computer Science
  • 刊物主题:Multimedia Information Systems; Computer Communication Networks; Data Structures, Cryptology and Information Theory; Special Purpose and Application-Based Systems;
  • 出版者:Springer US
  • ISSN:1573-7721
  • 卷排序:76
文摘
At present, the most reliable method to obtain end-user perceived quality is through subjective tests. In this paper, the impact of automatic region-of-interest (ROI) coding on perceived quality of mobile video is investigated. The evidence, which is based on perceptual comparison analysis, shows that the coding strategy improves perceptual quality. This is particularly true in low bit rate situations. The ROI detection method used in this paper is based on two approaches: (1) automatic ROI by analyzing the visual contents automatically, and (2) eye-tracking based ROI by aggregating eye-tracking data across many users, used to both evaluate the accuracy of automatic ROI detection and the subjective quality of automatic ROI encoded video. The perceptual comparison analysis is based on subjective assessments with 54 participants, across different content types, screen resolutions, and target bit rates while comparing the two ROI detection methods. The results from the user study demonstrate that ROI-based video encoding has higher perceived quality compared to normal video encoded at a similar bit rate, particularly in the lower bit rate range.

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