Reliable determination of object pose from line features by hypothesis testing

Abstract

To develop a reliable computer vision system, the employed algorithm must guarantee good output quality. In this study, to ensure the quality of the pose estimated from line features, two simple test functions based on statistical hypothesis testing are defined. First, an error function based on the relation between the line features and some quality thresholds is defined. By using the first test function defined by a lower bound of the error function, poor input can be detected before estimating the pose. After pose estimation, the second test function can be used to decide if the estimated result is sufficiently accurate. Experimental results show that the first test function can detect input with low qualities or erroneous line correspondences and that the overall proposed method yields reliable estimated results.