The emergence of depth sensors has made it possible to track not only monocular cues but also the actual depth values of the environment. This is especially useful in augmented reality solutions, where the position and orientation (pose) of the observer need to be accurately determined. Depth sensors have usually been used in augmented reality as mesh builders and in some cases as feature extractors for tracking. These methods are usually extensive and designed to operate by itself or in cooperation with other methods. We propose a systematic light-weight algorithm to supplement other mechanisms and we test it against a random algorithm and ground truth.