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Multi-view Geometry as a book category covers the mathematical and algorithmic foundations for recovering and reasoning about three-dimensional structure and camera motion from multiple images. Books in this category explain camera models and calibration, projective and epipolar geometry, homographies, stereo vision, structure-from-motion, bundle adjustment and related optimization techniques, and probabilistic and robust estimation methods. They combine linear algebra, projective geometry, and numerical optimization with practical topics such as feature matching, image rectification, dense reconstruction, and sensor fusion. Typical audiences are advanced undergraduates, graduate students, and practitioners in computer vision, robotics, photogrammetry, augmented reality, and computational photography who need both theoretical foundations and practical algorithms for 3D reconstruction and scene understanding from multiple viewpoints.

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