An example function is gluOrtho2D which defines a two dimensional orthographic projection matrix.
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In particular, the theory of Hilbert spaces and projection matrixes is heavily used.
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It is also possible to use this method in projection space by representing above inequality as determinant of a matrix and applying projection matrix to it.
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If \ bold p _ i is the right eigenvector of the matrix \ bold A corresponding to the eigenvalue \ lambda _ i, by building the projection matrix:
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The geometry is defined by a field of view angle ( in the'y'direction ), as well as an projection matrix for rendering transformations in a graphics pipeline.
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The system projects screen objects to 2D coordinates using the camera position ( using a projection matrix ) and uses these coordinates to impart movement constraints to the objects of the system.
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To recognize an object in an arbitrary input image, the paper detects features, and then uses RANSAC to find the affine projection matrix which best fits the unified object model to the 2D scene.
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By properties of a projection matrix, it has " p " = rank ( " X " ) eigenvalues equal to 1, and all other eigenvalues are equal to 0.
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One can construct a projection matrix \ mathbf { P } _ a ^ { \ perp }, which, when left and right multiplied by the signal covariance matrix, will reduce the interference term to zero.
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Practical applications of the projection matrix in regression analysis include leverage and Cook's distance, which are concerned with identifying influential observations, i . e . observations which have a large effect on the results of a regression.
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