SIFT-EST - a SIFT-based feature matching algorithm using homography estimation
| Autor: | Rolf-Rainer Grigat, Luh Putu Ayu Prapitasari, Arash Shahbaz Badr |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Computer science
business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-invariant feature transform Pattern recognition Local Features SIFT Informatik [004] Image Correspondences 004: Informatik Computer vision Artificial intelligence ddc:004 business Feature matching Feature Matching Homography (computer vision) Homography Estimation |
| Zdroj: | Proceedings of the 10th International Conference on Computer Vision Theory and Applications Vol. 3: 504-511 (2015) VISAPP (3) |
| Popis: | In this paper, a new feature matching algorithm is proposed and evaluated. This method makes use of features that are extracted by SIFT and aims at reducing the processing time of the matching phase of SIFT. The idea behind this method is to use the information obtained from already detected matches to restrict the range of possible correspondences in the subsequent matching attempts. For this purpose, a few initial matches are used to estimate the homography that relates the two images. Based on this homography, the estimated location of the features of the reference image after transformation to the test image can be specified. This information is used to specify a small set of possible matches for each reference feature based on their distance to the estimated location. The restriction of possible matches leads to a reduction of processing time since the quadratic complexity of the one-to-one matching is undermined. Due to the restrictions of 2D homographies, this method can only be applied to images that are related by pure-rotational transformations or images of planar object. |
| Databáze: | OpenAIRE |
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