Image Based Rendering (IBR) allows interactive scene exploration from images alone. However, despite considerable development in the area, one of the main obstacles to better quality and more realistic visualizations is the occurrence of visually disagreeable artifacts. In this paper we present a methodology to map out the perception of IBR-typical artifacts. This work presents an alternative to traditional image and video quality evaluation methods by using an EEG device to determine the implicit visual processes in the human brain. Our work demonstrates the distinct differences in the perception of different types of visual artifacts and the implications of these differences.

The way images are perceived by a human observer is becoming increasingly important in visual media, e.g. for (photo-) realistic image synthesis or memory-efficient encoding of large volumes of image/video data. Traditionally, perceived image quality is assessed by either using specially developed image quality metrics or by conducting user studies. In this paper, we investigate the use of electroencephalography as a tool for evaluating image quality. We demonstrate that the presence of artifacts reliably elicits a measurable response in the brain. We furthermore show that the reaction varies depending on the severity of artifacts, so that it may be used in order to objectively quantify image quality.