Two-step Kalman process for sensor and object motion estimation

Wilhelm Meier; Heinz-Dieter vom Stein

doi:10.1117/12.182870

17 August 1994 Two-step Kalman process for sensor and object motion estimation

Wilhelm Meier, Heinz-Dieter vom Stein

Proceedings Volume 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision; (1994) https://doi.org/10.1117/12.182870
Event: Spatial Information from Digital Photogrammetry and Computer Vision: ISPRS Commission III Symposium, 1994, Munich, Germany

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.

Citation Download Citation

Wilhelm Meier and Heinz-Dieter vom Stein "Two-step Kalman process for sensor and object motion estimation", Proc. SPIE 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision, (17 August 1994); https://doi.org/10.1117/12.182870

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