Estimation of Dense Displacement by Scale Invariant Polynomial Expansion of Heterogeneous Multi-View Images

Kazuki SHIBATA  Mehrdad PANAHPOUR TEHERANI  Keita TAKAHASHI  Toshiaki FUJII  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E100-D   No.9   pp.2048-2051
Publication Date: 2017/09/01
Publicized: 2017/06/14
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2016PCL0008
Type of Manuscript: Special Section LETTER (Special Section on Picture Coding and Image Media Processing)
Category: 
Keyword: 
sampling density,  dense displacement,  polynomial expansion,  scale invariant,  

Full Text: PDF>>
Buy this Article




Summary: 
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.