The 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. The authors 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, the authors propose a special initialization method using a second modified EKE.<>
Estimation of object and sensor motion in infrared image sequences
Proceedings of 1st International Conference on Image Processing ; 1 ; 568-572 vol.1
1994-01-01
460894 byte
Conference paper
Electronic Resource
English
Estimation of Object and Sensor Motion in Infrared Image Sequences
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