Deformation and illumination invariant feature point descriptor
Cita com:
hdl:2117/15198
Tipus de documentText en actes de congrés
Data publicació2011
Condicions d'accésAccés obert
Llevat que s'hi indiqui el contrari, els
continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
:
Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
Recent advances in 3D shape recognition have shown
that kernels based on diffusion geometry can be effectively
used to describe local features of deforming surfaces. In
this paper, we introduce a new framework that allows using
these kernels on 2D local patches, yielding a novel feature
point descriptor that is both invariant to non-rigid image
deformations and illumination changes.
In order to build the descriptor, 2D image patches are
embedded as 3D surfaces, by multiplying the intensity level
by an arbitrarily large and constant weight that favors
anisotropic diffusion and retains the gradient magnitude
information. Patches are then described in terms of a
heat kernel signature, which is made invariant to intensity
changes, rotation and scaling. The resulting feature point
descriptor is proven to be significantly more discriminative
than state of the art ones, even those which are specifically
designed for describing non-rigid image deformations.
CitacióMoreno, F. Deformation and illumination invariant feature point descriptor. A: IEEE Conference on Computer Vision and Pattern Recognition. "Proceedings of the 2011 IEEE Computer Society Conference on Computer Vision and Pattern Recognition". Colorado Springs: 2011, p. 1593-1600.
Versió de l'editorhttp://dx.doi.org/10.1109/CVPR.2011.5995529
Fitxers | Descripció | Mida | Format | Visualitza |
---|---|---|---|---|
1272-Deformatio ... ature-Point-Descriptor.pdf | 4,624Mb | Visualitza/Obre |