Department of Pattern Recognition

(eng): Illumination and view dependent texture provide ample information on the appearance of real materials at the cost of enormous data storage requirements. Hence, past research focused mainly on compression and modelling of these data, however, few papers have explicitly addressed the way in which humans perceive these compressed data. We analyzed human gaze information to determine appropriate texture statistics. These statistics were then exploited in a pilot illumination and view direction dependent data compression algorithm. Our results showed that taking into account local texture variance can increase compression of current methods more than twofold, while preserving original realistic appearance and allowing fast data reconstruction.