Title :
Error propagations for local bundle adjustment
Author :
Eudes, Alexandre ; Lhuillier, Maxime
Author_Institution :
LASMEA, Univ. Blaise Pascal, Aubiere, France
Abstract :
Local bundle adjustment (LBA) has recently been introduced to estimate the geometry of image sequences taken by a calibrated camera. Its advantage over standard (global) bundle adjustment is a great reduction of computational complexity, which allows real-time performances with a similar accuracy. However, no confidence measure on the LBA result such as uncertainty or covariance has yet been introduced. This paper introduces statistical models and estimation methods for uncertainty with two desirable properties: (1) uncertainty propagation along the sequence and (2) real-time calculation. We also explain why this problem is more complicated than it may appear at first glance, and we provide results on video sequences.
Keywords :
calibration; cameras; computational complexity; computational geometry; error statistics; estimation theory; image sequences; statistical analysis; camera calibration; computational complexity; error propagation; geometry estimation; image sequence; local bundle adjustment; real-time calculation; statistical model; uncertainty propagation; Cameras; Computer vision; Covariance matrix; Gaussian noise; Geometry; Image reconstruction; Image sequences; Least squares methods; Maximum likelihood estimation; Video sequences;
Conference_Titel :
Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on
Conference_Location :
Miami, FL
Print_ISBN :
978-1-4244-3992-8
DOI :
10.1109/CVPR.2009.5206824