Hierarchical fusion of color and depth information at partition level by cooperative region merging

Abstract

A high level scheme for information fusion to create hierarchical region-based image representations based on a region merging process is presented. The strategy is based on an iterative evolution where the different merging criteria work independently and cooperate at the partition level to obtain a further consensus that increases the reliability of the resulting partitions. This cooperative scheme is applied to the creation of hierarchical region-based representations of the image based on color and depth information. The proposed technique is compared with approaches using only one source of information or linear combinations of both, in datasets with ground truth as well as estimated disparity information.