Segmentation propagation during a camera saccade

In this paper, we present a method for propagating segmentation information across a saccade for a foveating camera. In particular, we take a region of interest from a wide-angle, low-fidelity image and propagate its segmentation information to a zoomed, high-fidelity image containing that region. Our method uses normalized greyscale templates to estimate the change in translation and magnification required to transform the segmented region. This process is useful for systems which detect regions of interest at low-fidelity and then perform a saccade to provide a high-fidelity view of that region of interest. We show how using this method increases the performance of an active object recognition system. Support for this work provided by NSF Grant IIS-9977206, NSF Grant EIA-0080124, and the W.M. Keck Foundation