Study on intelligent automatic tracking of moving targets in image sequences

Abstract

Several algorithms have been developed for the tracking of a moving target in image sequences. In these tracking algorithms, a centroid tracking algorithm and a correlation tracker are the most popular ones. The centroid tracker determines a target aim point by computing the geometric or intensity centroid of the target object based on the target segmentation method. In the correlation tracker, the motion of a block of pixels, termed a reference block, is estimated by looking for the most similar block of pixels in the subsequent frames. This dissertation studies on new automatic tracking algorithms of moving targets in image sequences, which include an intelligent centroid tracking algorithm and a robust correlation tracker. The performance of the centroid tracker depends on the following factors: (1) efficient real-time preprocessing technique, (2) exact segmentation algorithm, and (3) intelligent control of a tracking window size, etc.. Previous segmentation algorithms for the centroid tracker utilize only an intensity feature to segment a moving target from background images. And, they assume that all the related probability density functions of the target and the background are Gaussian ones in most cases. Ordinary segmentation algorithms often produce unstable results in real unconstrained outdoor scenes. In real tracking environments, the assumed Gaussian pdf`s are very different from those of real image sequences. Thus, it may be almost impossible to extract the target exactly from the cluttered image sequences. This dissertation proposes an efficient real-time preprocessing method in order to enhance the distinction between the objects of interest and their local backgrounds. In addition, a real-time adaptive segmentation method based on new distance features is also proposed for the intelligent centroid tracker. The novel features include spatial distances between the predicted center pixel of a target from a tracking filter and each pixel for the...