Abstract Model-Based Object Pose in 25 Lines of Code.pdfVIP

ModelBased Object Pose in
 Lines of Code Daniel F DeMenthon and Larry S Davis Computer Vision Laboratory Center for Automation Research University of Maryland College Park MD

Abstract In this paper we describe a method for nding the pose of an object from a single image We assume that we can detect and match in the image four or more noncoplanar feature points of the object and that we know their relative geometry on the object The method combines two algorithms the rst algorithm POS Pose from Orthography and Scaling approximates the perspective projection with a scaled orthographic projection and nds the rotation matrix and the translation vector of the object by solving a linear system the second algorithm POSIT POS with ITerations uses in its iteration loop the approximate pose found by POS in order to compute better scaled orthographic projections of the feature points then applies POS to these projections instead of the original image projections POSIT converges to accurate pose measurements in a few iterations POSIT can be used with many feature points at once for added insensitivity to measurement errors and image noise Compared to classic approaches making use of Newton s method POSIT does not require starting from an initial guess and computes the pose using an order of magnitude fewer oating point operations it may therefore be a useful alternative for realtime operation When speed is not an issue POSIT can be written in
lines or less in Mathematica the code is provided in an Appendix
Introduction Computation of the position and orientation of an object object pose using images of feature points when the geometric conguration of the features on the object is known a model has important applications such as calibration cartography tracking and object recognition Fischler and Bolles  have coined the term Perspective
n
Point problem or PnP problem for this type of problem with n feature points Rese