Abstract
The paper describes a kinematic model-based solution to estimate simultaneously the calibration parameters of the vision system and the full-motion of an object using a sequence of noisy images captured by a set of stereo affine cameras. Assuming a smooth motion, an Iterated Extended Kalman Filter (IEKF) is used to recursively estimate the cameras projection matrices and the object's full-motion over time. The estimator was developed having in mind the structure health monitoring of large structures of civil engineering domain, observed at long distance, in particular, of long deck suspension bridges. Results related to the performance evaluation, obtained by numerical simulation and with real experiments, are reported.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
