Tracking of moving objects in scenery using subspace projection using independent component analysis

A system is developed for tracking moving objects though natural scenery. A technique is presented for performing change detection on imagery to determine the difference between two images or a sequence of images. Form there an algorithm is presented to detect the presence of a new object and/or the deletion of objects. Then the application of a Variable Structure Interacting Multiple Model tracking filter is presented. The method of performing change detection is based upon the concept of image subspace projection. A set of basis image maps are formed when combined with a mixing matrix can recreate the original image. The subsequent images are then projected into the base image. The projected images is then subtracted from the original image to perform the change detection. Spatial Filtering is applied to increase the contrast between the change and the background then an adaptive filter is then applied to pass the locations of changes in the images into the tracking filter. Tracking is performed through the use of multiple motion models. The filter's motion models are adaptive added or deleted as required by the moving object's dynamics. The moving object's state is estimated through extended Kalman filtering.

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