In the conventional design approach to video quality metrics, the temporal nature of video is often considered only inadequately and also knowledge about the human visual system is required that is not readily available. In this thesis, I therefore propose a data-driven design methodology using multi-way data analysis for the design of video quality metrics that not only allows for the appropriate consideration of the temporal nature of video, but also leads to an increased prediction performance. «
In the conventional design approach to video quality metrics, the temporal nature of video is often considered only inadequately and also knowledge about the human visual system is required that is not readily available. In this thesis, I therefore propose a data-driven design methodology using multi-way data analysis for the design of video quality metrics that not only allows for the appropriate consideration of the temporal nature of video, but also leads to an increased prediction performanc... »
Translated abstract:
Designansätze für Videoqualitätsmetriken erfordern oft nicht nur ein umfassendes, meist nicht verfügbares Verständnis der menschlichen Wahrnehmung, sondern vernachlässigen ebenso oft den zeitlichen Charakter von Video. In dieser Dissertation wird deshalb ein datenorientierter Designansatz vorgestellt, der unter Verwendung von multi-way Datenanalyse nicht nur den zeitlichen Charakter von Video angemessen berücksichtigt, sondern darüber hinaus auch eine verbesserte Qualitätsbestimmung ermöglicht.