Metric Invariants for Camera Calibration: Designing algorithms from algebraic rank analysis - Softcover

Kim, Jun-Sik; Kweon, In So

Softcover

ISBN 10: 3846509884 ISBN 13: 9783846509883

Publisher: LAP LAMBERT Academic Publishing, 2011

Synopsis

Reconstructing a metric structure of a scene from images has been one of the important topics in computer vision. In this book, we focus on a simple diagonal rank-deficient form of a 2D metric invariant, a conic dual to the circular points. By manipulating image features to constrain the simple form algebraically, the metric reconstruction can be achieved. We start from second order curves such as concentric circles or confocal conics to be used as basic features. By simply subtracting them, affine and metric properties of a plane are recovered. The geometric meanings of the resulting subtraction matrices are also investigated. The idea of algebraically manipulating features extend to an ``addition method'' using human recognizable features such as a rectangle. Its parallelism and orthogonality enables us to obtain information of the scene structure. As a generalization, we propose a framework to unify the geometric constraints used in camera calibration and in metric reconstruction. We show that scene constraints can be converted into constraints of cameras, and that a flexible algorithm to metric-reconstruct scenes from images can be developed in the proposed unified framework.

About this title

About the Author

Jun-Sik KIM: Ph.D. in Electrical Engineering (2006) from KAIST, South Korea; Project Scientist at the Robotics Institute, Carnegie Mellon University, USA. In So KWEON: Ph.D. in Robotics (1990) from Carnegie Mellon University, USA; Professor at KAIST, South Korea; Director of the P3DigiCar research center; Editorial board member of IJCV.

Edition details

• Publisher: LAP LAMBERT Academic Publishing
• Publication date: 2011
• Language: English
• ISBN 10: 3846509884
• ISBN 13: 9783846509883
• Binding: Paperback
• Number of pages: 196