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 and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and 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 and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.
How to reconstruct scenes from images using geometry and algebra, with applications to computer vision.
How to reconstruct scenes from images using geometry and algebra, with applications to computer vision.
This book will help you tackle increasingly challenging computer vision problems .
The authors have backgrounds in geodesy and also long experience with development and research in computer vision, and this is the first book to present a joint approach from the converging fields of photogrammetry and computer vision.
This book introduces the geometry of 3-D vision, that is, the reconstruction of 3-D models of objects from a collection of 2-D images.
A modern treatment focusing on learning and inference, with minimal prerequisites, real-world examples and implementable algorithms.
Agarwala, A., Agrawala, M., Cohen, M., Salesin, D., and Szeliski, R. (2006). Photographing long scenes with multi-viewpoint panoramas. ACM Transactions on Graphics (Proc. SIGGRAPH 2006), 25(3):853–861. Agarwala, A., Dontcheva, M., ...
Coverage in this volume includes shape and texture, face and gesture, camera networks, face/gesture/action detection and recognition, learning, motion and tracking, human pose estimation, matching, face/gesture/action detection and ...
His theoretical account is illustratedwith the results of actual working programs.Three-Dimensional Computer Vision proposes solutions toproblems arising from a specific robotics scenario in which a system must perceive and act.
Closed-form matting, A. Levin, ht tp: / /www . wisdom .weizmann . ac . i1 / Nlevina/matting . tar . gz (Figures 2.2, ... 3.29, 3.30, and 3.33) 0 PatchMatch implementation, A. Adams et al., http : / /code . google . com/ p/ imagestack/ ...