Multiview Geometry for Camera Networks

Designing computer vision algorithms for camera networks requires an understanding of how images of the same scene from different viewpoints are related. This chapter introduces the basics of multiview geometry in computer vision, including image formation and camera matrices, epipolar geometry and the fundamental matrix, projective transformations, and N -camera geometry. We also discuss feature detection and matching, and describe basic estimation algorithms for the most common problems that arise in multiview geometry.