Interactive demonstrations of the locally adaptive fusion for combining objective quality measures

To automate quality monitoring of multimedia applications, objective quality measures for images and video content need to be designed. Objective quality measures that model the Human Visual System (HVS) have a disappointing performance, because the HVS is not sufficiently understood. Integrating machine learning (ML) techniques may increase the performance. Unfortunately, traditional ML is difficult to interpret. To this end, we developed the Locally Adaptive Fusion (LAF), for more flexible and reliable quality predictions. This manuscript proposes six interactive programs and a website that demonstrate the effectiveness of LAF, which complement the technical focus of the corresponding journal paper.