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- W2016030263 abstract "The scale invariant feature transform (SIFT) feature descriptor is invariant to image scale and location, and is robust to affine transformations and changes in illumination, so it is a powerful descriptor used in many applications, such as object recognition, video tracking, and gesture recognition. However, in noisy and non-rigid object recognition applications, especially for infrared human face recognition, SIFT-based algorithms may mismatch many feature points. This paper presents a star-styled window filter-SIFT (SWF-SIFT) scheme to improve the infrared human face recognition performance by filtering out incorrect matches. Performance comparisons between the SIFT and SWF-SIFT algorithms show the advantages of the SWF-SI FT algorithm through tests using a typical infrared human face database." @default.
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- W2016030263 date "2010-06-01" @default.
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- W2016030263 title "SWF-SIFT approach for infrared face recognition" @default.
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- W2016030263 doi "https://doi.org/10.1016/s1007-0214(10)70074-2" @default.
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