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Estimation of Dense Displacement by Scale Invariant Polynomial Expansion of Heterogeneous Multi-View Images
Kazuki SHIBATA Mehrdad PANAHPOUR TEHERANI Keita TAKAHASHI Toshiaki FUJII
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2017/09/01
Online ISSN: 1745-1361
Type of Manuscript: Special Section LETTER (Special Section on Picture Coding and Image Media Processing)
sampling density, dense displacement, polynomial expansion, scale invariant,
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Several applications for 3-D visualization require dense detection of correspondence for displacement estimation among heterogeneous multi-view images. Due to differences in resolution or sampling density and field of view in the images, estimation of dense displacement is not straight forward. Therefore, we propose a scale invariant polynomial expansion method that can estimate dense displacement between two heterogeneous views. Evaluation on heterogeneous images verifies accuracy of our approach.