The process of transcoding videos apart from being computationally intensive, can also be a rather complex procedure. The complexity refers to the choice of appropriate parameters for the transcoding engine, with the aim of decreasing video sizes, transcoding times and network bandwidth without degrading video quality beyond some threshold that event detectors lose their accuracy. This paper explains the need for transcoding, and then studies different video quality metrics. Commonly used algorithms for motion and person detection are briefly described, with emphasis in investigating the optimum transcoding configuration parameters. The analysis of
the experimental results reveals that the existing video quality metrics are not suitable for automated systems, and that the detection of persons is affected by the reduction of bit rate and resolution, while motion detection is more sensitive to frame rate.
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Publication Type = Conference or Workshop Item
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Subject = Computer Science: Image processing
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Subject = Computer Science
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Status = Published
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Subject = Computer Science: Video compression
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Subject = Computer Science: Multimedia systems
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Subject = Computer Science: Digital video
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DCU Faculties and Centres = Research Initiatives and Centres: INSIGHT Centre for Data Analytics
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Dublin City University ->
DCU Faculties and Centres = Research Initiatives and Centres
Suzanne Little,
Iveel Jargalsaikhan,
Marcos Nieto,
Michail Alexandros Kourtis,
Christos Xilouris,
Emmanouil Kafetzakis