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Statements

Subject Item
dbr:Scale-invariant_feature_operator
rdfs:label
Scale-invariant feature operator
rdfs:comment
In the fields of computer vision and image analysis, the scale-invariant feature operator (or SFOP) is an algorithm to detect local features in images. The algorithm was published by Förstner et al. in 2009.
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dbc:Applications_of_computer_vision dbc:Learning_in_computer_vision
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dbr:Harris_affine_region_detector dbr:Image_analysis dbc:Applications_of_computer_vision dbr:Hessian_affine_region_detector dbr:Feature_detection_(computer_vision) dbc:Learning_in_computer_vision n15:Ipb_algorithm.png dbr:Scale-invariant_feature_transform dbr:Corner_detection dbr:Maximally_stable_extremal_regions dbr:Computer_vision
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dbo:abstract
In the fields of computer vision and image analysis, the scale-invariant feature operator (or SFOP) is an algorithm to detect local features in images. The algorithm was published by Förstner et al. in 2009.
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wikipedia-en:Scale-invariant_feature_operator?oldid=1000100625&ns=0
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Subject Item
wikipedia-en:Scale-invariant_feature_operator
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dbr:Scale-invariant_feature_operator