<title>Multiple camera data fusion for accurate pose and scale recovery</title>

Abstract

This paper concerns the use of multiple cameras for accurate and noise-robust recovery of pose and scale parameters. Of particular interest is the recovery of pose and scale of vehicles in traffic scenes which, under normal conditions, are constrained to lie on the ground-plane. Several closed-form algorithms are described. The algorithms directly exploit the ground- plane constraint, and are applicable to an arbitrary number of image-to-model line matches. The importance of using multiple cameras is illustrated and the fusion of data from multiple cameras is shown to be simple and straightforward. The algorithms are tested extensively with both synthetic and real outdoor traffic images. They are found to be robust and perform satisfactorily with real images.