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  2. Signed distance function - Wikipedia

    en.wikipedia.org/wiki/Signed_distance_function

    In mathematics and its applications, the signed distance function or signed distance field (SDF) is the orthogonal distance of a given point x to the boundary of a set Ω in a metric space (such as the surface of a geometric shape), with the sign determined by whether or not x is in the interior of Ω.

  3. Bundle adjustment - Wikipedia

    en.wikipedia.org/wiki/Bundle_adjustment

    where (,) is the predicted projection of point on image and (,) denotes the Euclidean distance between the image points represented by vectors and . Because the minimum is computed over many points and many images, bundle adjustment is by definition tolerant to missing image projections, and if the distance metric is chosen reasonably (e.g ...

  4. Euclidean distance - Wikipedia

    en.wikipedia.org/wiki/Euclidean_distance

    In mathematics, the Euclidean distance between two points in Euclidean space is the length of the line segment between them. It can be calculated from the Cartesian coordinates of the points using the Pythagorean theorem , and therefore is occasionally called the Pythagorean distance .

  5. Color difference - Wikipedia

    en.wikipedia.org/wiki/Color_difference

    A very simple example can be given between the two colors with RGB values (0, 64, 0) ( ) and (255, 64, 0) ( ): their distance is 255. Going from there to (255, 64, 128) ( ) is a distance of 128. When we wish to calculate distance from the first point to the third point (i.e. changing more than one of the color values), we can do this:

  6. Scale-invariant feature transform - Wikipedia

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

    SIFT keypoints of objects are first extracted from a set of reference images [1] and stored in a database. An object is recognized in a new image by individually comparing each feature from the new image to this database and finding candidate matching features based on Euclidean distance of their feature vectors. From the full set of matches ...

  7. Line drawing algorithm - Wikipedia

    en.wikipedia.org/wiki/Line_drawing_algorithm

    Two rasterized lines. The colored pixels are shown as circles. Above: monochrome screening; below: Gupta-Sproull anti-aliasing; the ideal line is considered here as a surface. In computer graphics, a line drawing algorithm is an algorithm for approximating a line segment on discrete graphical media, such as pixel-based displays and printers.

  8. Lloyd's algorithm - Wikipedia

    en.wikipedia.org/wiki/Lloyd's_algorithm

    Lloyd's algorithm is usually used in a Euclidean space. The Euclidean distance plays two roles in the algorithm: it is used to define the Voronoi cells, but it also corresponds to the choice of the centroid as the representative point of each cell, since the centroid is the point that minimizes the average squared Euclidean distance to the ...

  9. Distance matrix - Wikipedia

    en.wikipedia.org/wiki/Distance_matrix

    In general, a distance matrix is a weighted adjacency matrix of some graph. In a network, a directed graph with weights assigned to the arcs, the distance between two nodes of the network can be defined as the minimum of the sums of the weights on the shortest paths joining the two nodes (where the number of steps in the path is bounded). [2]