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  2. Euclidean distance - Wikipedia

    en.wikipedia.org/wiki/Euclidean_distance

    The distance from a point to a plane in three-dimensional Euclidean space [7] The distance between two lines in three-dimensional Euclidean space [8] The distance from a point to a curve can be used to define its parallel curve, another curve all of whose points have the same distance to the given curve. [9]

  3. Eigenface - Wikipedia

    en.wikipedia.org/wiki/Eigenface

    A nearest-neighbour method is a simple approach for finding the Euclidean distance between two vectors, where the minimum can be classified as the closest subject. [ 3 ] : 590 Intuitively, the recognition process with the eigenface method is to project query images into the face-space spanned by eigenfaces calculated, and to find the closest ...

  4. Mean line segment length - Wikipedia

    en.wikipedia.org/wiki/Mean_line_segment_length

    In geometry, the mean line segment length is the average length of a line segment connecting two points chosen uniformly at random in a given shape. In other words, it is the expected Euclidean distance between two random points, where each point in the shape is equally likely to be chosen.

  5. Medoid - Wikipedia

    en.wikipedia.org/wiki/Medoid

    This example shows how Euclidean distance will calculate the distance between objects to determine how similar the items are. Note that most text embeddings will be at least a few hundred dimensions instead of just two. Euclidean distance is a standard distance metric used to measure the dissimilarity between two points in a multi-dimensional ...

  6. Triangulation (computer vision) - Wikipedia

    en.wikipedia.org/wiki/Triangulation_(computer...

    In the following, it is assumed that triangulation is made on corresponding image points from two views generated by pinhole cameras. The ideal case of epipolar geometry. A 3D point x is projected onto two camera images through lines (green) which intersect with each camera's focal point, O 1 and O 2. The resulting image points are y 1 and y 2.

  7. Scale-invariant feature transform - Wikipedia

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

    Finally, to avoid the expensive search required for finding the Euclidean-distance-based nearest neighbor, an approximate algorithm called the best-bin-first algorithm is used. [14] This is a fast method for returning the nearest neighbor with high probability, and can give speedup by factor of 1000 while finding nearest neighbor (of interest ...

  8. Euclidean space - Wikipedia

    en.wikipedia.org/wiki/Euclidean_space

    Projective space share with Euclidean and affine spaces the property of being isotropic, that is, there is no property of the space that allows distinguishing between two points or two lines. Therefore, a more isotropic definition is commonly used, which consists as defining a projective space as the set of the vector lines in a vector space of ...

  9. Foreground detection - Wikipedia

    en.wikipedia.org/wiki/Foreground_detection

    The following analyses make use of the function of V(x,y,t) as a video sequence where t is the time dimension, x and y are the pixel location variables. e.g. V(1,2,3) is the pixel intensity at (1,2) pixel location of the image at t = 3 in the video sequence.