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  2. Scale-invariant feature transform - Wikipedia

    en.wikipedia.org/wiki/Scale-invariant_feature...

    Hough transform identifies clusters of features with a consistent interpretation by using each feature to vote for all object poses that are consistent with the feature. When clusters of features are found to vote for the same pose of an object, the probability of the interpretation being correct is much higher than for any single feature.

  3. Spatial verification - Wikipedia

    en.wikipedia.org/wiki/Spatial_verification

    The goal is to keep the model with the highest number of matches and the main problem is the number of times you have to repeat the process to obtain the best estimate of the model. RANSAC set in advance the number of iterations of the algorithm. To specify scenes or objects, is commonly used affine transformations to perform the spatial ...

  4. Hough transform - Wikipedia

    en.wikipedia.org/wiki/Hough_transform

    The Hough transform as it is universally used today was invented by Richard Duda and Peter Hart in 1972, who called it a "generalized Hough transform" [3] after the related 1962 patent of Paul Hough. [ 4 ] [ 5 ] The transform was popularized in the computer vision community by Dana H. Ballard through a 1981 journal article titled " Generalizing ...

  5. Generalised Hough transform - Wikipedia

    en.wikipedia.org/wiki/Generalised_Hough_transform

    The generalized Hough transform (GHT), introduced by Dana H. Ballard in 1981, is the modification of the Hough transform using the principle of template matching. [1] The Hough transform was initially developed to detect analytically defined shapes (e.g., line, circle, ellipse etc.). In these cases, we have knowledge of the shape and aim to ...

  6. Randomized Hough transform - Wikipedia

    en.wikipedia.org/wiki/Randomized_Hough_Transform

    Hough transforms are techniques for object detection, a critical step in many implementations of computer vision, or data mining from images. Specifically, the Randomized Hough transform is a probabilistic variant to the classical Hough transform, and is commonly used to detect curves (straight line, circle, ellipse, etc.) [1] The basic idea of Hough transform (HT) is to implement a voting ...

  7. Perspective-n-Point - Wikipedia

    en.wikipedia.org/wiki/Perspective-n-Point

    Perspective-n-Point [1] is the problem of estimating the pose of a calibrated camera given a set of n 3D points in the world and their corresponding 2D projections in the image. The camera pose consists of 6 degrees-of-freedom (DOF) which are made up of the rotation (roll, pitch, and yaw) and 3D translation of the camera with respect to the world.

  8. Optical glass - Wikipedia

    en.wikipedia.org/wiki/Optical_glass

    Optical glass refers to a quality of glass suitable for the manufacture of optical systems such as optical lenses, prisms or mirrors.Unlike window glass or crystal, whose formula is adapted to the desired aesthetic effect, optical glass contains additives designed to modify certain optical or mechanical properties of the glass: refractive index, dispersion, transmittance, thermal expansion and ...

  9. Point-set registration - Wikipedia

    en.wikipedia.org/wiki/Point-set_registration

    Point set registration is the process of aligning two point sets. Here, the blue fish is being registered to the red fish. In computer vision, pattern recognition, and robotics, point-set registration, also known as point-cloud registration or scan matching, is the process of finding a spatial transformation (e.g., scaling, rotation and translation) that aligns two point clouds.