Search results for " LIOP"

showing 2 items of 2 documents

Rethinking the sGLOH Descriptor

2018

sGLOH (shifting GLOH) is a histogram-based keypoint descriptor that can be associated to multiple quantized rotations of the keypoint patch without any recomputation. This property can be exploited to define the best distance between two descriptor vectors, thus avoiding computing the dominant orientation. In addition, sGLOH can reject incongruous correspondences by adding a global constraint on the rotations either as an a priori knowledge or based on the data. This paper thoroughly reconsiders sGLOH and improves it in terms of robustness, speed and descriptor dimension. The revised sGLOH embeds more quantized rotations, thus yielding more correct matches. A novel fast matching scheme is a…

Cascade matching0209 industrial biotechnologyHistogram binarizationRFDComputer scienceGLOHComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyCNN descriptorLIOP020901 industrial engineering & automationMROGHArtificial IntelligenceRobustness (computer science)Keypoint matchingSIFTHistogram0202 electrical engineering electronic engineering information engineeringSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticabusiness.industryApplied MathematicsCognitive neuroscience of visual object recognitionPattern recognitionRotation invariant descriptorsGLOHMIOPComputational Theory and MathematicsKeypoint matching SIFT sGLOH RFDs LIOP MIOP MROGH CNN descriptors rotation invariant descriptors histogram binarization cascade matchingPrincipal component analysis020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftware
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Keypoint descriptor matching with context-based orientation estimation

2014

Abstract This paper presents a matching strategy to improve the discriminative power of histogram-based keypoint descriptors by constraining the range of allowable dominant orientations according to the context of the scene under observation. This can be done when the descriptor uses a circular grid and quantized orientation steps, by computing or providing a global reference orientation based on the feature matches. The proposed matching strategy is compared with the standard approaches used with the SIFT and GLOH descriptors and the recent rotation invariant MROGH and LIOP descriptors. A new evaluation protocol based on an approximated overlap error is presented to provide an effective an…

GLOHComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-invariant feature transformContext basedReference orientationImage descriptorLIOPDiscriminative modelMROGHHistogramKeypoint matchingSIFTComputer Science::MultimediaComputer visionInvariant (mathematics)MathematicsDominant orientationSettore INF/01 - Informaticabusiness.industryPattern recognitionGridLocal featureRotation invarianceComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingImage descriptors; Local features; Dominant orientation; Rotation invariance; Keypoint matching; SIFT; LIOP; MROGHComputer Vision and Pattern RecognitionArtificial intelligencebusiness
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