Linear pose estimation from points or lines

• Published in: IEEE transactions on pattern analysis and machine intelligence Vol. 25; no. 5; pp. 578 - 589
• Main Authors: Ansar, A., Daniilidis, K.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2003; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithm design and analysis; Algorithms; Application software; Cameras; Closed-form solution; Computer vision; Constraint optimization; Exact solutions; Image analysis; Intelligence; Iterative algorithms; Iterative methods; Mathematical models; Pattern analysis; Sensitivity analysis; Studies
• ISSN: 0162-8828; 1939-3539
• DOI: 10.1109/TPAMI.2003.1195992

Estimation of camera pose from an image of n points or lines with known correspondence is a thoroughly studied problem in computer vision. Most solutions are iterative and depend on nonlinear optimization of some geometric constraint, either on the world coordinates or on the projections to the image plane. For real-time applications, we are interested in linear or closed-form solutions free of initialization. We present a general framework which allows for a novel set of linear solutions to the pose estimation problem for both n points and n lines. We then analyze the sensitivity of our solutions to image noise and show that the sensitivity analysis can be used as a conservative predictor of error for our algorithms. We present a number of simulations which compare our results to two other recent linear algorithms, as well as to iterative approaches. We conclude with tests on real imagery in an augmented reality setup.