A basic problem in computer vision is to understand the structure of a real world scene given several images of it Techniques for solving this problem are taken from projective geometry & photogrammetry Here the authors cover the geometric principles & their algebraic representation in terms of camera projection matrices the fundamental matrix & the trifocal tensor The theory & methods of computation of these entities are discussed with real examples as is their use in the reconstruction of scenes from multiple images The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples & appendices) & significant new results which have appeared since the first edition Comprehensive background material is provided so readers familiar with linear algebra & basic numerical methods can understand the projective geometry & estimation algorithms presented & implement the algorithms directly from the book