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Proceedings Paper

Two-step Kalman process for sensor and object motion estimation
Author(s): Wilhelm Meier; Heinz-Dieter vom Stein
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Paper Abstract

This paper addresses the problem of estimating the sensor ego-motion and the motion of rigid objects in a monocular image sequence. It has been developed for a system processing infrared image sequences. These image sequences suffer from a high amount of noise and clutter. Therefore it is necessary to perform long-term image filtering. Since the sensor and the objects are subject to motion, the image sequences have to be motion compensated before filtering can take place. We present a technique based on the well known extended Kalman filter (EKF). It is adapted to the problem of estimating the sensor ego-motion via a correlation based tracking of the horizon. A general model for estimating rigid object motion with EKFs is developed. Since the performance of the EKf in this case strongly depends on its initialization, we propose a special initialization method using a second modified EKF.

Paper Details

Date Published: 17 August 1994
PDF: 7 pages
Proc. SPIE 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision, (17 August 1994); doi: 10.1117/12.182870
Show Author Affiliations
Wilhelm Meier, Univ. der Bundeswehr Hamburg (Germany)
Heinz-Dieter vom Stein, Univ. der Bundeswehr Hamburg (Germany)


Published in SPIE Proceedings Vol. 2357:
ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision

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