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  2. Bundle adjustment - Wikipedia

    en.wikipedia.org/wiki/Bundle_adjustment

    In photogrammetry and computer stereo vision, bundle adjustment is simultaneous refining of the 3D coordinates describing the scene geometry, the parameters of the relative motion, and the optical characteristics of the camera(s) employed to acquire the images, given a set of images depicting a number of 3D points from different viewpoints.

  3. Correspondence problem - Wikipedia

    en.wikipedia.org/wiki/Correspondence_problem

    The problem is made more difficult when the objects in the scene are in motion relative to the camera(s). A typical application of the correspondence problem occurs in panorama creation or image stitching — when two or more images which only have a small overlap are to be stitched into a larger composite image. In this case it is necessary to ...

  4. Graph cuts in computer vision - Wikipedia

    en.wikipedia.org/wiki/Graph_cuts_in_computer_vision

    As applied in the field of computer vision, graph cut optimization can be employed to efficiently solve a wide variety of low-level computer vision problems (early vision [1]), such as image smoothing, the stereo correspondence problem, image segmentation, object co-segmentation, and many other computer vision problems that can be formulated in terms of energy minimization.

  5. Image stitching - Wikipedia

    en.wikipedia.org/wiki/Image_stitching

    Two images stitched together. The photo on the right is distorted slightly so that it matches up with the one on the left. Image stitching or photo stitching is the process of combining multiple photographic images with overlapping fields of view to produce a segmented panorama or high-resolution image.

  6. Scale-invariant feature transform - Wikipedia

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

    SIFT features can essentially be applied to any task that requires identification of matching locations between images. Work has been done on applications such as recognition of particular object categories in 2D images, 3D reconstruction, motion tracking and segmentation, robot localization, image panorama stitching and epipolar calibration ...

  7. 3D reconstruction from multiple images - Wikipedia

    en.wikipedia.org/wiki/3D_Reconstruction_from...

    The correspondence problem, finding matches between two images so the position of the matched elements can then be triangulated in 3D space is the key issue here. Once you have the multiple depth maps you have to combine them to create a final mesh by calculating depth and projecting out of the camera – registration .

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  9. Hugin (software) - Wikipedia

    en.wikipedia.org/wiki/Hugin_(software)

    stitch large mosaics of images and photos, e.g. of long walls or large microscopy samples find control points and optimize parameters with the help of software assistants/wizards output several projection types, such as equirectangular (used by many full spherical viewers), mercator , cylindrical , stereographic , and sinusoidal