Image registration for foveated omnidirectional sensing

Abstract

This paper addresses the problem of registering high-resolution, small FOV images with low-resolution panoramic images provided by an omnidirectional catadioptric video sensor. Such systems may find application in surveillance and telepresence systems that require a large FOV and high resolution at selected locations. Although image registration has been studied in more conventional applications, the problem of registering omnidirectional and conventional video has not previously been addressed, and this problem presents unique challenges due to (i) the extreme differences in resolution between the sensors (more than a 16:1 linear resolution ratio in our application), and (ii) the resolution inhomogeneity of omnidirectional images. In this paper we show how a coarse registration can be computed from raw images using parametric template matching techniques. Further, we develop and evaluate robust feature-based and featureless methods for computing the full 2D projective transforms between the two images. We find that our novel featureless approach yields superior performance for this application.