Figure 1: Highly detailed animations can be difficult to reproduce on current display devices. Here, four frames from animations used to evaluate our apparent resolution enhancement are shown: (a) rendering of a ball textured with text; (b) rendering of a detailed assembly of fibers; (c) a rendered short film ("Big Buck Bunny" c by Blender Foundation); (d) high-resolution content captured with a video camera.
AbstractPresenting the variety of high resolution images captured by highquality devices, or generated on the computer, is challenging due to the limited resolution of current display devices. Our recent work addressed this problem by taking into account human perception. By applying a specific motion to a high-resolution image shown on a low-resolution display device, human eye tracking and integration could be exploited to achieve apparent resolution enhancement. To this end, the high-resolution image is decomposed into a sequence of temporally varying low-resolution images that are displayed at high refresh rates. However, this approach is limited to a specific class of simple or constant movements, i. e. "panning". In this work, we generalize this idea to arbitrary motions, as well as to videos with arbitrary motion flow. The resulting image sequences are compared to a range of other down-sampling methods.