Eye tracking based perceptual image inpainting quality analysis

Abstract

The objective of image inpainting is to perform a seamless completion of missing areas in images. Evaluating the perceptual quality of an inpainting algorithm must rely on features of the Human Visual System. Using eye-tracking experiments, we show that there is a strong correlation between inpainting quality and visual attention. By comparing gaze densities within and outside the hole regions of inpainted images, we show that discernible artifacts due to inpainting attract an unusual amount of visual attention. The gaze density within the hole, normalized with the gaze density of the same region from the unmodified image, provides a useful measure in comparing different inpainting processes and corroborates well with subjective rankings.