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  2. 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 ...

  3. Random sample consensus - Wikipedia

    en.wikipedia.org/wiki/Random_sample_consensus

    An advantage of RANSAC is its ability to do robust estimation [3] of the model parameters, i.e., it can estimate the parameters with a high degree of accuracy even when a significant number of outliers are present in the data set. A disadvantage of RANSAC is that there is no upper bound on the time it takes to compute these parameters (except ...

  4. Spatial verification - Wikipedia

    en.wikipedia.org/wiki/Spatial_verification

    Spatial verification is a technique in which similar locations can be identified in an automated way through a sequence of images. The general method involves identifying a correlation between certain points among sets images, using techniques similar to those used for image registration.

  5. 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 ...

  6. Circle Hough Transform - Wikipedia

    en.wikipedia.org/wiki/Circle_Hough_Transform

    The circle Hough Transform (CHT) is a basic feature extraction technique used in digital image processing for detecting circles in imperfect images. The circle candidates are produced by “voting” in the Hough parameter space and then selecting local maxima in an accumulator matrix. It is a specialization of the Hough transform.

  7. Scale-invariant feature transform - Wikipedia

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

    The determination of consistent clusters is performed rapidly by using an efficient hash table implementation of the generalised Hough transform. Each cluster of 3 or more features that agree on an object and its pose is then subject to further detailed model verification and subsequently outliers are discarded. Finally the probability that a ...

  8. PDA Alert! Julianne Hough Kisses Model Charlie Wilson ... - AOL

    www.aol.com/entertainment/pda-alert-julianne...

    Packing on the PDA! Julianne Hough was photographed kissing Charlie Wilson.. Julianne Hough and Brooks Laich: The Way They Were. Read article. The Dancing With the Stars alum, 33, and the 6-foot-3 ...

  9. Iterative closest point - Wikipedia

    en.wikipedia.org/wiki/Iterative_Closest_Point

    Transform the source points using the obtained transformation. Iterate (re-associate the points, and so on). Zhang [4] proposes a modified k-d tree algorithm for efficient closest point computation. In this work a statistical method based on the distance distribution is used to deal with outliers, occlusion, appearance, and disappearance, which ...