الفهرس 
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Abstract
In this thesis , we introduce an existing algorithm or tracking and estimating the motion parameters of a -igid body whose motion is confined to the XZ-plane . The algorithm adopts some assumptions that requires the previous knowledge of.some information about the moving object and the motion itself .
Then , we propose a new method based on Kalman filter for the estimation and tracking of a rigid body’s motion from a large sequence of noisy images. Two video sensors are used for acquiring range information. The problem considered is that of a 3-D rigid body undergoing unknown rotational and translational motion. The measurement datum consists of two sequences of noisy images of ( n ) object correspondence points. A recursive algorithm based on Cayley’s theorem is used to determine the motion parameters of the correspondence points from their position vectors. A modified Kalman filter model is used to track the motion of the body by updating the estimates of the body position with the measurements taken at each ime step .
Two modifications of the new algorithm are introduced at show a better behavior in terms of error in the timated positions of the moving object from its real sitions .
All the above algorithms are implemented and tested on a sample data with added white noise having a Gaussian
istribution , the testing methods are explained and results are shown in chapter five .