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Open collaboration on hybrid video quality models - VQEG joint effort group hybrid
Abstract : Several factors limit the advances on automatizing video quality measurement. Modelling the human visual system requires multi- and interdisciplinary efforts. A joint effort may bridge the large gap between the knowledge required in conducting a psychophysical experiment on isolated visual stimuli to engineering a universal model for video quality estimation under real-time constraints. The verification and validation requires input reaching from professional content production to innovative machine learning algorithms. Our paper aims at highlighting the complex interactions and the multitude of open questions as well as industrial requirements that led to the creation of the Joint Effort Group in the Video Quality Experts Group. The paper will zoom in on the first activity, the creation of a hybrid video quality model.
Keywords :
Databases
H.265 video coding
human visual system
hybrid video quality models
innovative machine learning algorithms
Joints
learning (artificial intelligence)
Measurement
psychophysical experiment
Quality assessment
Standards
video coding
video quality estimation
video quality experts group
video quality measurement
Video recording
Video sequences
visual stimuli
VQEG joint effort group hybrid
Cited literature [3 references]
https://hal.archives-ouvertes.fr/hal-00999662
Contributor : Harold Mouchère Connect in order to contact the contributor
Submitted on : Tuesday, June 3, 2014 - 7:29:34 PM
Last modification on : Wednesday, April 27, 2022 - 3:42:43 AM
Long-term archiving on: : Wednesday, September 3, 2014 - 1:06:04 PM
Contributor : Harold Mouchère Connect in order to contact the contributor
Submitted on : Tuesday, June 3, 2014 - 7:29:34 PM
Last modification on : Wednesday, April 27, 2022 - 3:42:43 AM
Long-term archiving on: : Wednesday, September 3, 2014 - 1:06:04 PM
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