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.
CitationCalderero, F.; Marques, F. Hierarchical fusion of color and depth information at partition level by cooperative region merging. A: IEEE International Conference on Acoustics, Speech and Signal Processing. "IEEE International Conference on Acoustics, Speech and Signal Processing 2009". Taipei, Taiwan: 2009, p. 973-976.
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