Detecting and Reconstructing 3D Mirror Symmetric Objects
Proceedings of the 12th European Conference on Computer Vision (ECCV) |
Published by Springer
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.