Three-dimensional pose tracking by image correlation and particle filtering

Abstract

This research presents an algorithm for three-dimensional (3-D) pose tracking of a rigid object by processing sequences of monocular images. The pose trajectory of the object is estimated by performing linear correlation between the current scene and a filter bank constructed from different views of a 3-D model of the target, which are created synthetically with computer graphics. The pose tracking is guided by particle filters that dynamically adapt the filter bank by taking into account the kinematics of the target in the scene. Experimental results obtained with the proposed algorithm in processing synthetic and real images are presented and discussed. These results show that the proposed algorithm achieves a higher accuracy of pose tracking in terms ofobjective metrics, in comparison with that of existing similar algorithms.