Open collaboration on hybrid video quality models - VQEG joint effort group hybrid
Résumé
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.
Mots clés
- visual stimuli
- VQEG joint effort group hybrid
- Video sequences
- Video recording
- video quality measurement
- video quality experts group
- video quality estimation
- video coding
- Standards
- Quality assessment
- psychophysical experiment
- Measurement
- learning (artificial intelligence)
- Joints
- innovative machine learning algorithms
- hybrid video quality models
- human visual system
- H.265 video coding
- Databases
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