Translator Disclaimer
Paper
30 September 2003 Recursive least squares approach to calculate motion parameters for a moving camera
Author Affiliations +
Proceedings Volume 5267, Intelligent Robots and Computer Vision XXI: Algorithms, Techniques, and Active Vision; (2003) https://doi.org/10.1117/12.514979
Event: Photonics Technologies for Robotics, Automation, and Manufacturing, 2003, Providence, RI, United States
Abstract
The increase in quality and the decrease in price of digital camera equipment have led to growing interest in reconstructing 3-dimensional objects from sequences of 2-dimensional images. The accuracy of the models obtained depends on two sets of parameter estimates. The first is the set of lens parameters - focal length, principal point, and distortion parameters. The second is the set of motion parameters that allows the comparison of a moving camera’s desired location to a theoretical location. In this paper, we address the latter problem, i.e. the estimation of the set of 3-D motion parameters from data obtained with a moving camera. We propose a method that uses Recursive Least Squares for camera motion parameter estimation with observation noise. We accomplish this by calculation of hidden information through camera projection and minimization of the estimation error. We then show how a filter based on the motion parameters estimates may be designed to correct for the errors in the camera motion. The validity of the approach is illustrated by the presentation of experimental results obtained using the methods described in the paper.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Samuel H. Chang, Joseph Fuller, Ali Farsaie, and Les Elkins "Recursive least squares approach to calculate motion parameters for a moving camera", Proc. SPIE 5267, Intelligent Robots and Computer Vision XXI: Algorithms, Techniques, and Active Vision, (30 September 2003); https://doi.org/10.1117/12.514979
PROCEEDINGS
9 PAGES


SHARE
Advertisement
Advertisement
Back to Top