Robust pose estimation in untextured environments for augmented reality applications

We present a robust camera pose estimation approach for stereo images captured in untextured environments. Unlike most of existing registration algorithms which are point-based and make use of intensities of pixels in the neighborhood, our approach imports line segments in registration process. With line segments as primitives, the proposed algorithm is capable to handle untextured images such as scenes captured in man-made environments, as well as the cases when there are large viewpoint changes or illumination changes. Furthermore, since the proposed algorithm is robust to large base-line stereos, there are improvements on the accuracy of 3D points reconstruction. With well-calculated camera pose and object positions in 3D space, we can embed virtual objects into existing scene with higher accuracy for realistic effects. In our experiments, 2D labels are embedded in the 3D scene space to achieve annotation effects as in AR.