Feature matching in stereo images encouraging uniform spatial distribution

Xiao Tan*, Changming Sun, Xavier Sirault, Robert Furbank, Tuan D. Pham

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    28 Citations (Scopus)

    Abstract

    Abstract Finding feature correspondences between a pair of stereo images is a key step in computer vision for 3D reconstruction and object recognition. In practice, a larger number of correct correspondences and a higher percentage of correct matches are beneficial. Previous researches show that the spatial distribution of correspondences are also very important especially for fundamental matrix estimation. So far, no existing feature matching method considers the spatial distribution of correspondences. In our research, we develop a new algorithm to find good correspondences in all the three aspects mentioned, i.e., larger number of correspondences, higher percentage of correct correspondences, and better spatial distribution of correspondences. Our method consists of two processes: an adaptive disparity smoothing filter to remove false correspondences based on the disparities of neighboring correspondences and a matching exploration algorithm to find more correspondences according to the spatial distribution of correspondences so that the correspondences are as uniformly distributed as possible in the images. To find correspondences correctly and efficiently, we incorporate the cheirality constraint under an epipole polar transformation together with the epipolar constraint to predict the potential location of matching point. Experiments demonstrate that our method performs very well on both the number of correct correspondences and the percentage of correct correspondences; and the obtained correspondences are also well distributed over the image space.

    Original languageEnglish
    Article number5365
    Pages (from-to)2530-2542
    Number of pages13
    JournalPattern Recognition
    Volume48
    Issue number8
    DOIs
    Publication statusPublished - 1 Aug 2015

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