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What is 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.Its name refers to the geometrical bundles of light rays originating from each 3D feature and converging on each camera's optical center, which are adjusted optimally according to an optimality criterion involving the corresponding image projections of all points.
How you will benefit
(I) Insights, and validations about the following topics:
Chapter 1: Bundle adjustment
Chapter 2: Levenberg-Marquardt algorithm
Chapter 3: Gauss-Newton algorithm
Chapter 4: Newton's method in optimization
Chapter 5: Iteratively reweighted least squares
Chapter 6: 3D reconstruction from multiple images
Chapter 7: Homography (computer vision)
Chapter 8: Chessboard detection
Chapter 9: Perspective-n-Point
Chapter 10: Powell's dog leg method
(II) Answering the public top questions about bundle adjustment.
(III) Real world examples for the usage of bundle adjustment in many fields.
Who this book is for
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of 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.Its name refers to the geometrical bundles of light rays originating from each 3D feature and converging on each camera's optical center, which are adjusted optimally according to an optimality criterion involving the corresponding image projections of all points.
How you will benefit
(I) Insights, and validations about the following topics:
Chapter 1: Bundle adjustment
Chapter 2: Levenberg-Marquardt algorithm
Chapter 3: Gauss-Newton algorithm
Chapter 4: Newton's method in optimization
Chapter 5: Iteratively reweighted least squares
Chapter 6: 3D reconstruction from multiple images
Chapter 7: Homography (computer vision)
Chapter 8: Chessboard detection
Chapter 9: Perspective-n-Point
Chapter 10: Powell's dog leg method
(II) Answering the public top questions about bundle adjustment.
(III) Real world examples for the usage of bundle adjustment in many fields.
Who this book is for
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Bundle Adjustment.
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