Abstract
We present a system that detects 3D mirror-symmetric objects
in images and then reconstructs their visible symmetric parts. Our
detection stage is based on matching mirror symmetric feature points and
descriptors and then estimating the symmetry direction using RANSAC.
We enhance this step by augmenting feature descriptors with their affine deformed
versions and matching these extended sets of descriptors. The
reconstruction stage uses a novel edge matching algorithm that matches
symmetric pairs of curves that are likely to be counterparts. This allows
the algorithm to reconstruct lightly textured objects, which are problematic
for traditional feature-based and intensity-based stereo matchers.
@inproceedings {Sinha-ECCV12,
author = "Sudipta N. Sinha and Krishnan Ramnath and Richard Szeliski",
title = "Detecting and Reconstructing 3D Mirror Symmetric Objects",
booktitle = "European Conference on Computer Vision (ECCV 2012)",
location = "Firenze, Italy",
month = "October",
year = "2012",
}
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