Distortion-Induced Saliency Shifts in Video

Visual saliency modelling is of fundamental importance in modern video processing and its applications. Our previous eye-tracking study revealed that signal distortions caused by editing, compression, or transmission alter gaze patterns and consequently induce saliency shifts in both spatial and temporal domains. Saliency shifts provide crucial insights into viewers' behavioural responses to video distortions, facilitating the perception-based optimisation of video algorithms. However, the spatio-temporal saliency shifts and their measurable effects on perception related applications remain largely unexplored. In this paper, we first investigate the measurement of distortion-induced saliency shifts (DSS) in videos and analyse DSS behaviours as functions of video content, time order and critical distortion disruption. Second, based on our findings, we construct three vision models to quantitatively simulate distinct DSS behaviours and integrate them into a comprehensive DSS behaviour model. Finally, we demonstrate that the computational DSS model can enhance emerging video technologies.