This thesis describes the theoretical bases, development and testing of an integrated moving object detection framework in 2D and 3D scenes. The detection problem is analyzed in stationary and non-stationary camera sequences and different algorithms are developed for each case. Two methods are proposed in stationary camera sequences: background extraction followed by differencing and thresholding, and motion detection using optical flow field calculated by &ldquo / Kanade-Lucas Feature Tracker&rdquo / . For non-stationary camera sequences, different algorithms are developed based on the scene structure and camera motion characteristics. In planar scenes where the scene is flat or distant from the camera and/or when camera makes rotations only, a method is proposed that uses 2D parametric registration based on affine parameters of the dominant plane for independently moving object detection. A modified version of the 2D parametric registration approach is used when the scene is not planar but consists of a few number of planes at different depths, and camera makes translational motion. Optical flow field segmentation and sequential registration are the key points for this case. For 3D scenes, where the depth variation within the scene is high, a parallax rigidity based approach is developed for moving object detection. All these algorithms are integrated to form a unified independently moving object detector that works in stationary and non-stationary camera sequences and with different scene and camera motion structures. Optical flow field estimation and segmentation is used for this purpose.

Στο πλαίσιο της εργασίας αυτής προτείνεται μια τεχνική η οποία προσπαθεί να κάνει ταυτόχρονα εκτίμηση της οπτικής ροής καθώς επίσης και διαμέριση της σκηνής σε διαφορετικά κινούμενα σώματα. Συγκεκριμένα προτείνεται η λύση μιας ακολουθίας προβλημάτων ελαχιστοποίησης. Κάθε πρόβλημα ελαχιστοποίησης προσπαθεί να απομονώσει κάποιο κινούμενο σώμα από την σκηνή και εκτιμά για αυτό μία ταχύτητα. Τα αποτελέσματα που προέκυψαν από την εφαρμογή της τεχνικής σε προβλήματα εκτίμησης της οπτικής ροής διαφορετικής πολυπλοκότητας δείχνουν ότι η επίδοση της προτεινόμενης τεχνικής είναι ικανοποιητική. / In this thesis, a method, which tries to estimate the optical flow field, and segment the scene at the same time, is suggested. Specifically, a series of minimization problems are solved. Each of these minimization problems, tries to isolate a moving object from the scene, and estimate for it a velocity. The results from applying the suggested method in several optical flow estimation problems, with varying complexities, show that the performance of the method is very promising.