In this paper we address the problem of cubic panorama image dataset compression. Two state-of-the-art approaches,
namely: H.264/MPEG4 AVC and Dirac video codec, are used and compared for the application of
virtual navigation in image based representations of real world environments. Different prediction structures and
Group Of Pictures (GOP) sizes are investigated and compared on this new type of visual data. Based on the
obtained results, as well as the requirements of the system, an efficient prediction structure and bitstream syntax
are proposed. The concept of Epipolar geometry is introduced and a method to facilitate efficient disparity
estimation is suggested.