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Alignment and Tracking using Graphics

This paper explores an optimized variant of mutual-information based alignment that uses graphics hardware to accelerate tracking of a 3D object in a video scene. It is designed for fast operation on computers that are equipped with graphics hardware. The algorithms described use a histogram-based method for computing the mutual information between object and scene. The gradient of mutual information is ascended in an eeort to estimate the pose parameters of the object within the scene. This method has linear cost in the number of pixels and the number of his-togram bins. The computer graphics techniques used to implement the registration algorithm are described. The general approach is to map the problem of computing three-dimensional scene information onto readily available computer graphics accelerator hardware. This increases the algorithm's performance signiicantly. Initial experiments are described where the experimental system is used to track moderate-speed manual motions of the test object in a high-contrast scene.