Hessian affine

14 examples (0.01 sec)
  • However, for some structured scenes, like buildings, the Hessian affine detector performs very well.
  • The Hessian affine region detector is a feature detector used in the fields of computer vision and image analysis.
  • Like the Harris affine detector, Hessian affine interest regions tend to be more numerous and smaller than other detectors.
  • The Hessian affine detector responds well to textured scenes in which there are a lot of corner-like parts.
  • The Hessian affine also uses a multiple scale iterative algorithm to spatially localize and select scale & affine invariant points.
  • Like other feature detectors, the Hessian affine detector is typically used as a preprocessing step to algorithms that rely on identifiable, characteristic interest points.
  • For a single image, the Hessian affine detector typically identifies more reliable regions than the Harris-Affine detector.
  • Furthermore, using these initially detected points, the Hessian affine detector uses an iterative shape adaptation algorithm to compute the local affine transformation for each interest point.
  • Overall, the Hessian affine detector performs second best to MSER.
  • The Hessian affine detector algorithm is almost identical to the Harris affine region detector.
  • In Mikolajczyk et al., six region detectors are studied (Harris-affine, Hessian-affine, MSER, edge-based regions, intensity extrema, and salient regions).
  • From the detection invariance point of view, feature detectors can be divided into fixed scale detectors such as normal Harris corner detector, scale invariant detectors such as SIFT and affine invariant detectors such as Hessian-affine.
  • Other detectors that are affine-invariant include Hessian affine region detector, Maximally stable extremal regions, Kadir-Brady saliency detector, edge-based regions (EBR) and intensity-extrema-based regions (IBR).
  • The Hessian affine detector is part of the subclass of feature detectors known as affine-invariant detectors: Harris affine region detector, Hessian affine regions, maximally stable extremal regions, Kadir-Brady saliency detector, edge-based regions (EBR) and intensity-extrema-based (IBR) regions.