Extended VQM model for predicting 3D video quality considering ambient illumination context

To speed-up the proliferation of advanced 3-Dimensional (3D) technologies into the consumer market, the influence of these technologies on the perception of 3D video should be determined. Currently, this can only be achieved using either subjective assessment techniques or 2D objective quality evaluation models. Even though the subjective assessment techniques are better than the objective models from the accuracy point of view, they are time consuming and costly. Thus, 2D objective quality evaluation models correlating with Human Visual System (HVS) should be used to predict the 3D video quality perception of users in a reliable way with less effort. Video Quality Metric (VQM), which is a standardized 2D objective quality measurement model due to its well correlation with HVS, is used to predict 3D video quality perception of users reliably. However, ambient illumination context of the viewing environment, which has an effect on 3D video quality perception, is not considered in the quality assessments by VQM. Content adaptation is one of the key applications that need to use the perceived 3D quality assessments under different ambient illumination conditions at regular basis for ensuring improved video experience of users. Therefore, the standardized VQM model is extended using ambient illumination context and content related contexts (i.e., motion, structural feature, and luminance contrast) to predict 3D video quality measurement under a particular ambient illumination condition. The results prove that the extended VQM model can be efficiently utilized to predict the video quality perception of 3D video under a particular ambient illumination condition.