Descriptor-Free Smooth Feature-Point Matching for Images Separated by Small/Mid Baselines

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 exp...

• Type: Conference
• Year: 2007
• Where: ACIVS
• Authors: Ping Li, Dirk Farin, Rene Klein Gunnewiek, Peter H. N. de With
• Keywords: ACIVS 2007, Computer Vision, Feature Points, Feature-point Matching Algorithm, Smoothness Constraint