Computer Graphics
TU Braunschweig

Robust Feature Matching in General Multi-Image Setups

Robust Feature Matching in General Multi-Image Setups

We present a robust feature matching approach that considers features from more than two images during matching. Traditionally, corners or feature points are matched between pairs of images. Starting from one image, corresponding features are searched in the other image. Yet, often this two-image matching is only a subproblem and actually robust matches over multiple views and/ or images acquired at several instants in time are required. In our feature matching approach we consider the multi-view video data modality and find matches that are consistent in three images. Requiring neither calibrated nor synchronized cameras, we are able to reduce the percentage of wrongly matched features considerably. We evaluate the approach for different feature detectors and their natural descriptors and show an application of our improved matching approach for optical flow calculation on unsynchronized stereo sequences.

Author(s):Anita Sellent, Martin Eisemann, Marcus Magnor
Published:February 2011
Journal:Journal of WSCG Vol. 19
Project(s): Multi-Image Correspondences  Image-space Editing of 3D Content  Reality CG 

  title = {Robust Feature Matching in General Multi-Image Setups},
  author = {Sellent, Anita and Eisemann, Martin and Magnor, Marcus},
  journal = {Journal of {WSCG}},
  volume = {19},
  pages = {1--8},
  month = {Feb},
  year = {2011}