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  2. Category:Geometry in computer vision - Wikipedia

    en.wikipedia.org/wiki/Category:Geometry_in...

    Geometry in computer vision is a sub-field within computer vision dealing with geometric relations between the 3D world and its projection into 2D image, typically by means of a pinhole camera. Common problems in this field relate to Reconstruction of geometric structures (for example, points or lines) in the 3D world based on measurements in ...

  3. Geometric feature learning - Wikipedia

    en.wikipedia.org/wiki/Geometric_feature_learning

    Geometric feature learning is a technique combining machine learning and computer vision to solve visual tasks. The main goal of this method is to find a set of representative features of geometric form to represent an object by collecting geometric features from images and learning them using efficient machine learning methods.

  4. 3D Morphable Model - Wikipedia

    en.wikipedia.org/wiki/3D_Morphable_Model

    In computer vision and computer graphics, the 3D Morphable Model (3DMM) is a generative technique that uses methods of statistical shape analysis to model 3D objects. The model follows an analysis-by-synthesis approach over a dataset of 3D example shapes of a single class of objects (e.g., face, hand).

  5. Homography (computer vision) - Wikipedia

    en.wikipedia.org/wiki/Homography_(computer_vision)

    In the field of computer vision, any two images of the same planar surface in space are related by a homography (assuming a pinhole camera model). This has many practical applications, such as image rectification , image registration , or camera motion—rotation and translation—between two images.

  6. Fundamental matrix (computer vision) - Wikipedia

    en.wikipedia.org/wiki/Fundamental_matrix...

    In computer vision, the fundamental matrix is a 3×3 matrix which relates corresponding points in stereo images.In epipolar geometry, with homogeneous image coordinates, x and x′, of corresponding points in a stereo image pair, Fx describes a line (an epipolar line) on which the corresponding point x′ on the other image must lie.

  7. Perspective-n-Point - Wikipedia

    en.wikipedia.org/wiki/Perspective-n-Point

    Efficient PnP (EPnP) is a method developed by Lepetit, et al. in their 2008 International Journal of Computer Vision paper [9] that solves the general problem of PnP for n ≥ 4. This method is based on the notion that each of the n points (which are called reference points) can be expressed as a weighted sum of four virtual control points ...

  8. Image rectification - Wikipedia

    en.wikipedia.org/wiki/Image_rectification

    If the images to be rectified are taken from camera pairs without geometric distortion, this calculation can easily be made with a linear transformation.X & Y rotation puts the images on the same plane, scaling makes the image frames be the same size and Z rotation & skew adjustments make the image pixel rows directly line up [citation needed].

  9. 2D computer graphics - Wikipedia

    en.wikipedia.org/wiki/2D_computer_graphics

    2D computer graphics is the computer-based generation of digital images—mostly from two-dimensional models (such as 2D geometric models, text, and digital images) and by techniques specific to them. It may refer to the branch of computer science that comprises such techniques or to the models themselves. Raster graphic sprites (left) and masks