Alignment of cubic-panorama image datasets using epipolar geometry

Panoramic images are a new type of visual data that provide many new possibilities as compared to the classic planar images. Tele-presence and virtual navigation are examples of such interesting applications. In order to enable smooth navigation across different view points, we propose a method for aligning cubic-panorama image datasets by using the concept of epipolar geometry. Unlike existing methods, which are limited to a pair of panoramas, our approach is accurate and applicable on datasets with large number of panoramic images. Also for the first time, a measure is introduced in order to enable objective evaluations.