Texture-Independent Feature-Point Matching (TIFM) from Motion Coherence

Abstract. This paper proposes a novel and efficient feature-point matching algorithm for finding point correspondences between two uncalibrated images. The striking feature of the proposed algorithm is that the algorithm is based on the motion coherence/smoothness constraint only, which states that neighboring features in an image tend to move coherently. In the algorithm, the correspondences of feature points in a neighborhood are collectively determined in a way such that the smoothness of the local motion field is maximized. The smoothness constraint does not rely on any image feature, and is self-contained in the motion field. It is robust to the camera motion, scene structure, illumination, etc. This makes the proposed algorithm texture-independent and robust. Experimental results show that the proposed method outperforms existing methods for feature-point tracking in image sequences.

• Type: Conference
• Year: 2007
• Where: ACCV
• Authors: Ping Li, Dirk Farin, Rene Klein Gunnewiek, Peter H. N. de With
• Keywords: ACCV 2007, Algorithm, Computer Vision, Feature-point Matching Algorithm, Motion Coherence/smoothness Constraint