Search

In this paper, we propose a two-stage weighting based perceptual quality assessment framework for asymmetrically distorted stereoscopic video (SV) sequences by temporal binocular rivalry. Firstly, a traditional 2D image quality assessment (IQA) method is employed to measure spatial distortion, and the temporal distortion is evaluated by the magnitude differences between motion vectors of distorted and reference video frames. Secondly, the structural strength (SS) computed by gradient map and the motion energy (ME) computed by frame difference map are used to estimate the intensity of visual stimulus in spatial and temporal domain respectively. Then, SS and ME are considered as the importance indexes to combine the quality scores of spatial and temporal distortion to estimate perceived distortion of single-view video sequences, which is denoted as the first-stage weighting. Finally, considering that the difference of intensity of visual stimulus between two eyes results in binocular rivalry, a novel temporal binocular rivalry inspired weighting method is designed to integrate the quality scores of left- and right-views for the final visual quality prediction of SV sequences, which is denoted as the second-stage weighting. Experimental results on Waterloo-IVC SV quality databases show that several specific examples of 2D-IQA methods within the proposed framework can obtain highly competitive performance over other existing ones. [ABSTRACT FROM AUTHOR]

• A motion variation based quality pooling method for 3D video quality assessment. • The method relies on the edge energy information and motion energy information. • Temporal information is effective in estimating monocular energy. The two-stage framework has been widely used in objective image/video quality assessment (IQA/VQA) methods, which includes local quality measurement and global quality pooling. Most of the existing IQA/VQA methods dedicate to local quality degradation modeling. Nevertheless, the significant pooling strategies are often neglected, especially in the quality assessment methods for asymmetrically distorted 3D video sequences. In this paper, motivated by the fact that the perceptual visual information might be affected by the visual masking due to motion suppression, a novel pooling strategy is proposed for visual quality assessment of asymmetrically distorted 3D video sequences by considering the motion variation-based perceptual visual information (MVPVI). In specific, to extract valuable visual information of video sequences, the proposed method computes the motion energy information (MEI) and edge energy information (EEI) by quantifying the frame difference map and the gradient map, respectively. Furthermore, in order to simulate the phenomenon of motion suppression in local motion scenes, where the perceptual information of low-attentional regions might be neglected by the human visual system (HVS), the proposed method first employs the coefficient of variation (CV) to determine the type of motion (local or global) in consecutive frames. Then, the perceptual visual information of the two cases is quantified. Finally, to simulate the role of HVS as an optimal information extractor, the estimated perceptual visual information of each single-view video sequence is used as the weighting factor for the quality pooling of left and right-view video sequences. Extensive comparison experiments conducted on Waterloo-IVC 3D video quality databases demonstrate that the proposed pooling strategy outperforms other relevant pooling strategies, and it achieves better performance than state-of-the-art 3D-IQA/VQA methods when combined with 2D-IQA/VQA methods. [ABSTRACT FROM AUTHOR]