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Quasi-Dense Matching between Perspective and Omnidirectional Images

Abstract : In this paper, we propose a match propagation algorithm between perspective and omnidirectional images of same scene consisting of planes, which does not require a rectification for the omnidirectional image. First, a linear transformation is introduced to identify the area containing the corresponding point candidates. Then, a geometric invariant is computed as a constraint for quasi-dense matching. Finally, combining the computed geometric invariant with a best-first strategy of Lhuillier and Quan (2002), the quasi-dense point correspondences are calculated. The experiments with real data show that the algorithm of this paper has good performance.
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https://hal.inria.fr/inria-00326782
Contributor : Peter Sturm <>
Submitted on : Sunday, October 5, 2008 - 3:10:03 PM
Last modification on : Thursday, April 11, 2019 - 2:34:02 PM
Long-term archiving on: : Monday, October 8, 2012 - 2:01:09 PM

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Lingling Lu, Yihong Wu. Quasi-Dense Matching between Perspective and Omnidirectional Images. Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications - M2SFA2 2008, Andrea Cavallaro and Hamid Aghajan, Oct 2008, Marseille, France. ⟨inria-00326782⟩

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