Shape context, the Glossary

Table of Contents

1. 18 relations: Affine transformation, Canny edge detector, Chi-squared test, Gaussian filter, Hungarian algorithm, Inflection point, Jitendra Malik, K-medoids, K-nearest neighbors algorithm, Least squares, MNIST database, Moore–Penrose inverse, Nearest neighbor search, Outline of object recognition, Serge Belongie, Statistical classification, System of linear equations, Thin plate spline.

Affine transformation

In Euclidean geometry, an affine transformation or affinity (from the Latin, affinis, "connected with") is a geometric transformation that preserves lines and parallelism, but not necessarily Euclidean distances and angles.

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Canny edge detector

The Canny edge detector is an edge detection operator that uses a multi-stage algorithm to detect a wide range of edges in images.

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Chi-squared test

A chi-squared test (also chi-square or test) is a statistical hypothesis test used in the analysis of contingency tables when the sample sizes are large.

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Gaussian filter

In electronics and signal processing, mainly in digital signal processing, a Gaussian filter is a filter whose impulse response is a Gaussian function (or an approximation to it, since a true Gaussian response would have infinite impulse response).

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Hungarian algorithm

The Hungarian method is a combinatorial optimization algorithm that solves the assignment problem in polynomial time and which anticipated later primal–dual methods.

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Inflection point

In differential calculus and differential geometry, an inflection point, point of inflection, flex, or inflection (rarely inflexion) is a point on a smooth plane curve at which the curvature changes sign.

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Jitendra Malik

Jitendra Malik is an Indian-American academic who is the Arthur J. Chick Professor of Electrical Engineering and Computer Sciences at the University of California, Berkeley.

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K-medoids

The -medoids problem is a clustering problem similar to k-means.

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K-nearest neighbors algorithm

In statistics, the k-nearest neighbors algorithm (k-NN) is a non-parametric supervised learning method first developed by Evelyn Fix and Joseph Hodges in 1951, and later expanded by Thomas Cover.

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Least squares

The method of least squares is a parameter estimation method in regression analysis based on minimizing the sum of the squares of the residuals (a residual being the difference between an observed value and the fitted value provided by a model) made in the results of each individual equation.

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MNIST database

The MNIST database (Modified National Institute of Standards and Technology database) is a large database of handwritten digits that is commonly used for training various image processing systems.

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Moore–Penrose inverse

In mathematics, and in particular linear algebra, the Moore–Penrose inverse of a matrix, often called the pseudoinverse, is the most widely known generalization of the inverse matrix.

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Nearest neighbor search

Nearest neighbor search (NNS), as a form of proximity search, is the optimization problem of finding the point in a given set that is closest (or most similar) to a given point.

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Outline of object recognition

Object recognition – technology in the field of computer vision for finding and identifying objects in an image or video sequence.

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Serge Belongie

Serge Belongie is a professor of Computer Science at the University of Copenhagen, where he also serves as the head of the.

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Statistical classification

When classification is performed by a computer, statistical methods are normally used to develop the algorithm.

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System of linear equations

In mathematics, a system of linear equations (or linear system) is a collection of two or more linear equations involving the same variables.

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Thin plate spline

Thin plate splines (TPS) are a spline-based technique for data interpolation and smoothing.

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References

[1] https://en.wikipedia.org/wiki/Shape_context

Also known as ShapeContext.