Compression of photo collections using geometrical information

This paper proposes a novel scheme for the joint compression of photo collections framing the same object or scene. The proposed approach starts by locating corresponding features in the various images and then exploits a Structure from Motion algorithm to estimate the geometric relationships between the various images and their viewpoints. Then it uses 3D information and warping to predict images one from the other. Furthermore, graph algorithms are used to compute minimum weight topologies and identify the ordering of the input images that maximizes the efficiency of prediction. The obtained data is fed to a modified HEVC coder to perform the compression. Experimental results show that the proposed scheme outperforms competing solutions and can be efficiently employed for the storage of large image collections in the virtual exploration of architectural landmarks or in photo sharing websites.