Descriptor-free smooth feature-point matching for images separated by small/mid baselines

  • Authors:

  • Ping Li;Dirk Farin;Rene Klein Gunnewiek;Peter H. N. De With

  • Affiliations:

  • Eindhoven University of Technology;Eindhoven University of Technology;Philips Research Eindhoven;LogicaCMG Netherlands B.V.

  • Venue:
  • ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
  • Year:
  • 2007

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Abstract

Most existing feature-point matching algorithms rely on photometric region descriptors to distinct and match feature points in two images. In this paper, we propose an efficient feature-point matching algorithm for finding point correspondences between two uncalibrated images separated by small or mid camera baselines. The proposed algorithm does not rely on photometric descriptors for matching. Instead, only the motion smoothness constraint is used, which states that the correspondence vectors within a small neighborhood usually have similar directions and magnitudes. The correspondences of feature points in a neighborhood are collectively determined in such a way that the smoothness of the local correspondence field is maximized. The smoothness constraint is self-contained in the correspondence field and is robust to the camera motion, scene structure, illumination, etc. This makes the entire point-matching process texture-independent, descriptor-free and robust. The experimental results show that the proposed method performs much better than the intensity-based block-matching technique, even when the image contrast varies clearly across images.