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.
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Li, P., Farin, D., Klein Gunnewiek, R., de With, P.H.N. (2007). Texture-Independent Feature-Point Matching (TIFM) from Motion Coherence. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds) Computer Vision – ACCV 2007. ACCV 2007. Lecture Notes in Computer Science, vol 4843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76386-4_75
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DOI: https://doi.org/10.1007/978-3-540-76386-4_75
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