An iterative Bayesian technique for Dense Image Point Matching

نویسندگان

  • Christian B. U. Perwass
  • Gerald Sommer
چکیده

We present a conceptually simple algorithm for dense image point matching between two multi-modal (e.g. color) images. The algorithm is based on the assumption that correct image point matches satisfy locally a particular statistical distribution. Through an iterative evaluation of a local probability measure, global constraints are taken into account and the most likely set of image point matches is found. An advantage of this approach is that no information about the camera geometries, as for example the epipoles, has to be known. Therefore, the algorithm can be used for stereo matching and optic flow.

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تاریخ انتشار 2002