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.<>


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    Title :

    Estimation of object and sensor motion in infrared image sequences


    Contributors:


    Publication date :

    1994-01-01


    Size :

    460894 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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