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Projecte matriculat
Títol: Analysis and Evaluation of No-Reference Video Quality Assesment using Neural Networks
Director: TARRÉS RUIZ, Francesc
Departament: TSC
Títol: Analysis and Evaluation of No-Reference Video Quality Assesment using Neural Networks
Data inici oferta: 07-01-2020 Data finalització oferta: 07-09-2020
Estudis d'assignació del projecte:
GR ENG SIS TELECOMUN
| Tipus: Individual | |
| Lloc de realització: EETAC | |
| Paraules clau: | |
| Video analysis, Video Quality Assesment, Deep Learning, Python, Machine Learning | |
| Descripció del contingut i pla d'activitats: | |
| The measure of the subjective quality of video is a difficult task that requires the
preparation of a large series of testings defining examples, groups of people, control groups, etc. Therefore, some video analysis techniques have been developed in order to predict the 'subjective' quality of a video. These techniques a divided in 2 groups: reference and no-reference VQA algortihms, depending of the requirement of the original video in the prediction algorithm. When the original video is not available the problem becomes specially complex but it is of great interest in many applications. In this thesis we will explore some strategies based on using deep learning in order to obtain Video Quality Assessment without a Reference Signal. The main approach will be to develope a neural architecture that will be trained using well known VQA methods such as VMAF or other methods. Once trained, the system will have to predict the quality of new videos without reference |
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| Orientació a l'estudiant: | |
| Image Processing, Python, Machine Learning, Deep Learning, Keras | |
| Horari d'atenció a estudiants per a l'assignació de projecte: |
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