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Quality assessment of user-generated video using camera motion

Guo, Jinlin, Gurrin, Cathal orcid logoORCID: 0000-0003-2903-3968, Hopfgartner, Frank orcid logoORCID: 0000-0003-0380-6088, Zhang, Zhenxing and Lao, Songyang (2013) Quality assessment of user-generated video using camera motion. In: The19th International MultiMedia Modeling Conference, 9 Jan 2012, Huangshan, China.

With user-generated video (UGV) becoming so popular on theWeb, the availability of a reliable quality assessment (QA) measure of UGV is necessary for improving the users’ quality of experience in videobased application. In this paper, we explore QA of UGV based on how much irregular camera motion it contains with low-cost manner. A blockmatch based optical flow approach has been employed to extract camera motion features in UGV, based on which, irregular camera motion is calculated and automatic QA scores are given. Using a set of UGV clips from benchmarking datasets as a showcase, we observe that QA scores from the proposed automatic method and subjective method fit well. Further, the automatic method reports much better performance than the random run. These confirm the satisfaction of the automatic QA scores indicating the quality of the UGV when only considering visual camera motion. Furthermore, it also shows that the UGV quality can be assessed automatically for improving the end users quality of experience in video-based applications.
Item Type:Conference or Workshop Item (Poster)
Event Type:Conference
Uncontrolled Keywords:Quality Assessment; User-generated Video; Irregular Camera Motion; Optical Flow
Subjects:Computer Science > Multimedia systems
Computer Science > Digital video
DCU Faculties and Centres:Research Institutes and Centres > CLARITY: The Centre for Sensor Web Technologies
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:17530
Deposited On:10 Jan 2013 11:41 by Jinlin Guo . Last Modified 11 Oct 2018 11:00

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