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WxBS: Wide Baseline Stereo Generalizations

Dmytro Mishkin and Jiri Matas and Michal Perdoch and Karel Lenc
Proceedings of the British Machine Vision Conference (BMVC)
September 2015

Abstract

We present a generalization of the wide baseline two view matching problem - WX BS, where X stands for a different subset of "wide baselines" in acquisition conditions such as geometry, illumination, sensor and appearance. We introduce a novel dataset of ground- truthed image pairs which include multiple "wide baselines" and show that state-of-the- art matchers fail on almost all image pairs from the set. A novel matching algorithm for addressing the WX BS problem is introduced and we show experimentally that the WXBS-M matcher dominates the state-of-the-art methods both on the new and existing datasets.


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@InProceedings{eth_biwi_01222,
  author = {Dmytro Mishkin and Jiri Matas and Michal Perdoch and Karel Lenc},
  title = {WxBS: Wide Baseline Stereo Generalizations},
  booktitle = {Proceedings of the British Machine Vision Conference (BMVC)},
  year = {2015},
  month = {September},
  pages = {12.1-12.12},
  editor = {Xianghua Xie and Mark W. Jones and and Gary K. L. Tam},
  publisher = {BMVA Press},
  keywords = {WBS, matching, challenging, mutlimodal}
}