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@ {Inproceedings

author = {Maykel Pérez and Luis Salgado and Jon Arróspide and Javier Marinas and Marcos Nieto },

title = {Multi-Camera Very Wide Baseline Feature Matching Based On View-Adaptive Junction Detection },

year = {2012-09-05 },

keys = { },

pages = {74- 77 },

abstract = {This paper presents a strategy for solving the feature matching problem in calibrated very wide-baseline camera settings. In this kind of settings, perspective distortion, depth discontinuities and occlusion represent enormous challenges. The proposed strategy addresses them by using geometrical information, specifically by exploiting epipolar-constraints. As a result it provides a sparse number of reliable feature points for which 3D position is accurately recovered. Special features known as junctions are used for robust matching. In particular, a strategy for refinement of junction end-point matching is proposed which enhances usual junction-based approaches. This allows to compute cross-correlation between perfectly aligned plane patches in both images, thus yielding better matching results. Evaluation of experimental results proves the effectiveness of the proposed algorithm in very wide-baseline environments. },

issn = { },

in = {IEEE 2012 Third International Conference on Emerging Security Technologies },